the
Cambridge
Future Scholar
Research Programme
Explore your passions
through a research
course.
The Cambridge Future Scholar Programme offers online research courses for high school students. Each course has 2–5 students and is taught by current faculty from leading universities. These include the University of Cambridge, the University of Oxford, MIT, Harvard, Stanford, and select Ivy League universities.
In addition, each spring, summer, and fall round offers more than 100 unique research courses. Students can explore subjects across STEM, Business, Social Sciences, and the Humanities.
Watch this video to learn more about the Future Scholar programme.
Programme Outcome
A Semester's Worth of
Teaching
Students receive 13 weeks of lectures and supervision from Oxbridge or Ivy League faculty mentors and PhD teaching assistants. The curriculum mirrors first-year courses at the mentors’ universities.
An Independent Research
Project
Students complete an original research paper under the guidance of an Oxbridge or Ivy League faculty mentor. The project aims to prepare students to pursue publication in undergraduate or industry-level journals.
A Signed Evaluation
Report
Each student receives an evaluation report from their Oxbridge or Ivy League faculty mentor. The report highlights the student’s performance throughout the programme.
A Letter of
Recommendation
Students can also request a tailored letter of recommendation. Their Oxbridge or Ivy League faculty mentor writes the letter to reflect their academic experience and performance.
Download
the Fall 2026
Prospectus for
• Programme structure
• Research course catalogue
• Mentor biographies
• Tuition & Scholarship
Oxbridge Level Writing Centre
Our writing centre is staffed by Oxbridge students and alumni. It is always available to provide prompt feedback on your writing.
Independent Ethics Review
Committee
Research involving human subjects often requires an ERC review. This helps ensure that experiments adhere to research ethics. CCIR’s independently run ERC is led by Dr McClelland at the University of Cambridge.
Journal Publication Guidance
Publishing requires know-how. Our expert team helps you transition from high school to academic writing. In addition, we actively assist you in getting your work published.
Our academic advisors maintain a database of publications. This helps us identify where and how to showcase your work. We also help you avoid predatory academic forums and support you as you publish in legitimate journals and conferences.
Conducting In-person Research
at CCIR Lab in Boston
The Cambridge Centre for International Research (CCIR) is proud to announce the opening of the CCIR Lab in Boston, surrounded by R&D centers of Pfizer, Novartis, and the MIT campus.
Starting in Spring 2025, current and future CCIR student researchers from both the Cambridge Future Scholar Research Programme and the 1-on-1 Research Mentorship Programme will be able to conduct their own research and experiments (or choose from a list of pre-approved experiments), at the state-of-the-art lab near the campus of MIT and major biotechnology hubs.
CCIR student researchers can reserve the CCIR Lab in Boston through the CCIR Academics Team at no additional cost.
CCIR’s PhD level lab managers will also be on site to supervise each student researcher’s project.
Located in the vibrant Kendall Square, the CCIR Lab in Boston is situated next to the R&D center of global pharmaceutical companies Pfizer and Novartis, Google’s Boston office, and the iconic MIT Great Dome, on the busy Main Street in Cambridge, MA.
Founded in 1832, the building have became home of a host of innovations of technology advancement, including the original birthplace of Polaroid and the world’s first long distance phone call between Thomas Watson and Alexander Graham Bell.
With millions of new funding from leading life sciences corporate sponsors (including Johnson & Johnson, Biogen, Pfizer, and Bayer), the lab has become a hub of innovation for mostly Harvard and MIT affiliated startups. Recent ventures at the lab included Affinivax, later acquired by GSK for $3.3 billion for its groundbreaking vaccine design.
For nearly 200 years, this facility has been the forefront of driving revolutionary advancements in life sciences.
Course Structure
Each 13-week research course is divided into two parts
Lecture Weeks (1 - 7)
Build up your foundation of knowledge
With support from your mentor and teaching assistants (TAs), you will build knowledge in your research field. Each week includes one hour of lectures from your mentor. You will also receive one hour of seminar discussion with your TA and a 30-minute office hour upon request.
Research Weeks (8 - 13)
Plan and execute your own research project
The research phase begins with a research and methodology session. After that, you will transition to self-directed work. Lecture sessions become research workshops during this phase. Meanwhile, TA sessions become writing sessions.
Programme Details
1 Hour
weekly session with faculty mentor and PhD TA
30 Minutes
weekly 1-on-1 Office Hour on request
Unlimited
correspondence and guidance from faculty mentor and CCIR Academics Team
2 to 5
students admitted per course
1:2
average faculty to student ratio
<20%
Overall Acceptance Rate
173 Unique Research Courses,
Designed and Taught by Ivy League/Oxbridge Faculty
Each course is designed and taught by current Oxbridge and Ivy League faculty.
For full professor mentor biographies and course descriptions, please download the latest prospectus.
Harvard (Harvard Medical School) | Department of Cardiology
In this research course, we explore the principles of developmental biology and stem cell biology. Students study organ development, such as the heart, and discuss genome engineering using CRISPR-Cas9, a novel genetic modification tool.
The course encourages students to think creatively about how cells develop into organisms. Students also explore how researchers study these processes experimentally, edit genes, and use animal models to analyse in vivo data.
Harvard (Harvard Medical School) | Department of Cardiology
Traditional biology often studies millions of cells at once and reports a single average. However, important discoveries can emerge when scientists study cells individually.
This course introduces technologies that are transforming modern biology, from single-cell sequencing to spatial omics. Students learn how these tools help scientists understand development, disease, and tissue organisation.
Through the course, students explore how researchers identify cell types and track changes over time. They also examine how different cells interact within complex systems, including the brain, immune system, and cancer. For students interested in biology, this course provides an introduction to an exciting methodological shift in the life sciences.
Brown | BioMed MCB Department
In this research course, each student reads, analyses, and presents assigned peer-reviewed research articles in cell and developmental biology. This field explores how interacting processes shape an organism’s size, structure, and other features throughout its life cycle.
Topics include asymmetric cell division, cell signalling and metabolism, cellular specification and differentiation, and mRNA translation. Students also explore embryonic development, germ cell and stem cell development, and cancer regulation.
Cambridge | Cambridge Institute for Medical Research
Injury to the brain and spinal cord can have devastating consequences. This is because adult neurons in the central nervous system do not repair their nerve fibres.
This research course explores the cellular and molecular biology of the nervous system. It focuses particularly on the regrowth of nerve fibres after an acute injury, a process known as axon regeneration.
Through the independent research project, students gain hands-on experience analysing real experimental data from fluorescence microscopy of neurons. They also learn to present scientific results.
Cambridge | Cambridge Institute for Medical Research
As technology advances, scientists are exploring increasingly complex questions. Much of this research focuses on the relationship between genes, proteins, and biological processes.
This research course gives students hands-on experience with computational tools. They use these tools to predict and analyse the effects of mutations. In addition, students learn how computational approaches can complement experimental research and support innovation in drug discovery and disease prevention.
Cambridge | Cambridge Institute for Medical Research
Explore the genome through this hands-on research course in modern genomics data analysis. Focusing on RNA sequencing, students investigate how gene expression patterns reveal molecular processes behind cell function, development, and responses to environmental changes.
Students work directly with real, publicly available RNA datasets. Through this work, they gain practical experience in experimental design and data interpretation. They also learn to analyse complex datasets, identify meaningful biological trends, and develop evidence-based scientific narratives.
By the end of the course, students will be able to navigate genomics data with greater confidence. They will connect quantitative analysis to real-world biological insights and prepare to contribute to cutting-edge life sciences research.
Princeton | Department of Molecular Biology
In this course, students receive a comprehensive introduction to protein biochemistry. They explore several decades of technological advances, including polymerase chain reaction (PCR), recombinant protein expression technologies, CRISPR/Cas9 gene editing, and advances in optical microscopy.
The course combines fundamental concepts in molecular biology and biochemistry with seminal literature in the field. This research has led to major scientific breakthroughs and changed how textbooks are written.
Students will explore protein-based machines through independent research projects. These projects use basic molecular biology and biochemical techniques, if available, and/or computational AI-based tools.
Cambridge | Department of Pharmacology
RNA is more than a simple intermediary between DNA and proteins. It is a dynamic and versatile molecule that regulates gene expression and controls cellular behaviour. As a result, RNA has become a powerful tool in modern biological research and medicine.
This research course introduces students to the fundamental principles of RNA biology. Students then explore how researchers have applied these principles to control gene expression in both research and clinical settings.
Oxford | Department of Biochemistry
In this research course, we explore genetics through computational and data science techniques. Students analyse large quantities of data using these advanced methods. Through this process, they learn to observe and analyse molecular events across the genomes of biological systems.
Cambridge | Department of Genetics
In this research course, students explore the role of genetics in understanding and combating infectious diseases. They also develop skills in computational analysis, known as bioinformatics. These skills help students understand infection mechanisms at the gene and protein levels.
Cambridge | Department of Medicine
Pandemics pose a major threat to public health. They can also have severe consequences for global economies. Therefore, it is important to study the factors that drive their emergence and spread.
This research course explores infectious diseases from a genetic perspective. Students examine whole-genome genetic data to better understand the molecular mechanisms behind the spread and evolution of pathogens that cause infectious diseases.
Cambridge | Department of Pharmacology
In this course, students learn the basic principles of cancer biology. They also explore how to use bioinformatics tools to analyse health data.
Students discuss the hallmarks of cancer to better understand findings from data-mining exercises. In addition, they explore large-scale biological datasets using different bioinformatics tools and platforms.
These findings help students identify genes that may serve as biomarkers or have potential therapeutic applications.
Cambridge | Department of Pharmacology
For fifty years, predicting how a protein folds from its sequence was one of biology’s hardest problems. That changed when the AI system AlphaFold solved this challenge. The breakthrough was recognised with the 2024 Nobel Prize in Chemistry.
In this research course, students explore how AI systems such as AlphaFold predict protein structures. They also learn how generative models can create new structures.
Each student completes an independent design project. For example, they might engineer a small protein to bind a cancer target, such as the oncogene KRAS or the immunotherapy checkpoint PD-L1. Students then evaluate their designs critically, interpret the results, and identify the strengths and limitations of these AI tools.
Cambridge | School of Clinical Medicine
Biomedical data analysis plays an essential role in understanding human health and disease. Today, researchers work with data from many sources, including multi-omics, imaging, genomics, and phenotypic profiles.
In this research course, students explore how to analyse these complex datasets. They also learn about AI-driven tools that are reshaping modern biomedical research.
By the end of the course, students will have a solid understanding of biological data analysis and its applications in biomedical research.
Oxford | Department of Computer Science
Proteins are molecular machines that help cells communicate, grow, defend themselves, and respond to their environment. Their functions depend on their amino-acid sequences and how they fold, move, and interact with other molecules. Mutations can also change how proteins behave.
This research course introduces students to computational structural biology through accessible biological questions. Students gain hands-on experience working with real molecular data. In addition, they explore molecular simulation and machine learning. The course also examines what these methods can and cannot establish.
Cambridge | Cancer Research UK Cambridge Institute
Cancer involves more than rogue cells. The surrounding environment also influences how tumours grow, spread, and respond to treatment.
This course introduces students to the biology of the tumour microenvironment. It also explores advanced imaging techniques that help researchers study processes that are otherwise difficult to observe.
Students examine tumour heterogeneity, metabolism, therapy resistance, and translational research models. They also learn how fluorescence microscopy, Raman microscopy, and photoacoustic imaging reveal clinically relevant information.
This course is particularly suitable for students interested in cancer biology, biomedical imaging, and how laboratory discoveries can inform medical practice.
Cambridge | Department of Chemistry
Drug resistance is not just a bacterial problem. It is also a leading cause of cancer treatment failure. But how do these different biological systems evade modern medicines?
This research course explores the evolutionary and molecular mechanisms of drug resistance. It connects the fields of oncology and infectious diseases. Students learn the fundamental principles of pharmacology, targeted therapies, and evolutionary biology. As a result, they gain a better understanding of why diseases relapse and how modern science works to overcome resistance.
Oxford | Department of Biochemistry
DNA damage takes many forms. If left unrepaired, it can lead to mutations, cell death, or cancer. To prevent these outcomes, our cells rely on the DNA damage response (DDR). This complex network detects, signals, and repairs DNA damage with remarkable precision.
This cellular defence system helps maintain genomic stability. It is also central to our understanding of cancer development and treatment.
The course explores a key question in modern biology and medicine: how do cells protect their genetic code from daily damage, and what happens when these defences fail? Students investigate the mechanisms of the DNA damage response. They learn how cells detect, signal, and repair different forms of DNA damage.
Harvard | Joslin Diabetes Center
Throughout this research course, students explore advanced strategies and technologies used in drug discovery. The course focuses on treatments that target metabolism.
Drug development continues to advance, offering several approaches. These include novel drug design, high-throughput screening methods, and precision medicine techniques.
Through these methods, students develop the knowledge and skills needed to engage in current research. They also explore how their work can contribute to the development of next-generation drugs aimed at combating metabolic diseases.
Harvard | Massachusetts General Hospital
Regenerative medicine aims to restore the function of damaged organs and tissues. It uses stem cells and biologically compatible materials known as biomaterials.
In this course, students examine the basics of stem cell biology and explore different types of biomaterials. They also discuss current tissue engineering strategies and commercially available tissue engineering products.
Finally, each student conducts a research project. Participants develop their own hypothesis and explore tissue engineering strategies to restore a type of tissue of their choice.
Cambridge | Department of Veterinary Medicine
This course introduces students to bacterial genomics and the global challenge of antimicrobial resistance (AMR). Students explore resistance genes, horizontal gene transfer, and advanced DNA sequencing techniques. They also develop practical bioinformatics skills for AMR surveillance.
Beyond the theory, the course examines strategies to combat AMR. These include responsible antibiotic use, alternative therapies, and global initiatives.
Through hands-on exercises, discussions, and collaborative projects, students analyse real-world genomic data. They also learn to propose solutions to AMR challenges.
UC Berkeley | University & Jepson Herbaria
This hands-on, interdisciplinary research course introduces students to biological diversity. It also explores the different ways scientists study and understand biodiversity.
Biodiversity involves more than the number of species in an area. It also includes how species interact, function, and vary across space and time.
Students learn how scientists measure biodiversity using different metrics. These include species richness, evenness, abundance, beta diversity, and functional diversity. Each metric reveals different information about ecosystems.
The course illustrates these concepts with examples from plants, animals, and fungi. Through these examples, students explore the complexity of life and its importance on Earth.
Cambridge | Department of Veterinary Medicine
Zoonotic diseases occur when pathogens spread from animals to humans. They pose a major global health threat and account for nearly 75 percent of emerging infectious diseases.
This research course explores how pathogens adapt to new hosts. Students use whole-genome sequencing and bioinformatics tools to investigate these molecular and evolutionary processes. They also study important cases, including SARS-CoV-2, avian influenza, and bovine tuberculosis.
Through these examples, students learn how genetic changes allow pathogens to cross species boundaries. This knowledge helps them understand and address critical global health challenges.
Oxford | Centre of Medicine Discovery
Rare diseases affect people across diverse biological systems. However, many remain poorly understood. This can lead to delayed diagnoses, limited treatment options, and significant emotional and social challenges.
This research course explores the science behind rare diseases. Students use Congenital Dyserythropoietic Anaemia 1 (CDA-1) as a case study. They also examine the real-world impact of rare diseases on patients, families, and healthcare systems.
By working closely with a CDA-1 patient charity and researchers, students develop skills in research, scientific writing, and communication. In addition, they explore the ethical and societal dimensions of rare disease medicine.
Harvard | Harvard Medical School
What is the nervous system, and how does it shape our thoughts, behaviours, and mental processes? This research course introduces students to neuroscience. It explores the structure and function of the nervous system, from the molecular to the cognitive level.
Students also examine the biological principles behind neural activity, behaviour, and mental processes. Key topics include synaptic transmission, neuroplasticity, sensory and motor systems, and the biological foundations of learning and memory.
Stanford | Department of Psychiatry and Behavioral Sciences
This research course explores the role of artificial intelligence (AI) in neuroscience. Students examine how tools such as computer vision and computational modelling help researchers study behaviour. These tools can track social interactions with greater precision and link them to patterns of brain activity.
As a result, researchers can better understand how experiences influence social behaviour and how responses change with context.
For example, students investigate how algorithms detect interactions between two animals. They also explore how these tools identify aggressive behaviour and link observations to specific brain circuits.
These case studies help students consider fundamental questions. How do experiences rewire the brain? Why do some animals become more social while others become more withdrawn?
Stanford | Department of Psychiatry and Behavioral Sciences
Can a computer decode thoughts from the brain’s electrical activity? This research course explores how mathematics, data science, and artificial intelligence (AI) reveal patterns in neural signals.
Students investigate how scientists predict decisions, reconstruct speech, and decode movement. They also explore how machine learning and computational models help researchers build brain–computer interfaces.
By the end of the course, students will understand how neural data can provide meaningful insights into perception, memory, behaviour, and the mind.
Oxford | Centre for Neural Circuit and Behavior
Why do we behave the way we do? This course explores the question through a central challenge in modern biology: understanding how genes shape neurons, how neurons form circuits, and how those circuits produce behaviour.
Students study gene expression, epigenetics, neural signalling, and brain network organisation. They also examine the biological foundations of behaviours such as learning, feeding, social interaction, and stress responses.
Along the way, students encounter modern research tools, including CRISPR, RNA sequencing, and optogenetics. For those interested in neuroscience, genetics, and the biological foundations of behaviour, this course offers a rigorous and engaging introduction.
Cambridge | Cavendish Laboratory
Recent advances in deep learning and large medical imaging datasets are changing how clinicians interpret CT and MRI scans.
This research course covers image processing, anatomical context, and advanced AI methods. Students explore how these methods improve the reliability and transparency of medical imaging models.
Through hands-on Python programming, students build AI pipelines. They work with real clinical imaging datasets, from data preprocessing to model training and explainability analysis.
Cambridge | Department of Clinical Neurosciences
Why does your brain miss the obvious, remember the wrong detail, or respond before you are even aware of it? This research course explores the hidden mechanisms behind attention, memory, perception, and decision-making.
Students investigate these processes through real experiments. Designed for motivated high school students interested in psychology, neuroscience, cognitive science, and research, the course provides an introduction to experimental cognitive psychology.
It also prepares students for future research opportunities in university laboratories and related academic fields.
Oxford | Department of Experimental Psychology
This research course explores the building blocks of human intelligence through cognitive psychology. Students examine fundamental processes such as attention, memory, and learning.
They then investigate how these abilities contribute to more complex processes. These include decision-making, problem-solving, and abstract thinking, which help shape intelligent behaviour.
Overall, the course aims to give students a thorough understanding of key topics in cognitive psychology. It also provides opportunities to connect theoretical and experimental knowledge. In addition, students learn about the tools and approaches researchers use to study cognition.
Oxford | Department of Experimental Psychology
What is the relationship between art and the human psyche? Why does art exist, and why do people need it? This research course explores these questions through an interdisciplinary approach to understanding the arts.
Students examine insights from psychology and neuroscience. They also explore practical applications of art in psychotherapy and mental health work. The course focuses on art as an expression of our psychological worlds and the relationship between art and the human psyche.
Harvard (Harvard Medical School) | Beth Israel Deaconess Medical Center, Boston
The blood-brain barrier plays an important role in neuroscience. It protects the brain from harmful substances in the blood while allowing essential nutrients to pass through.
In this research course, students explore key concepts in cellular and molecular medicine, neuroscience, and genetics. The course focuses specifically on the blood-brain barrier (BBB) and its critical role in brain function.
Harvard (Harvard Medical School) | Beth Israel Deaconess Medical Center, Boston
This research course introduces students to the fundamental principles of stem cell biology and regenerative medicine. It explores the growing field of regenerative medicine and its potential applications.
Students learn about the role of stem cells in biological research and clinical practice. This foundation helps prepare them for further study or a career in stem cell science and regenerative medicine. In addition, students gain an introduction to one of the most promising and rapidly evolving areas of modern biology.
Oxford | Department of Physiology Anatomy and Genetics
Tissue loss caused by injury, disease, or aging can lead to permanent impairments. This is because many organs, especially the brain, have a limited ability to regenerate.
Stem cells can renew themselves and develop into specialized cells. As a result, they offer promising ways to repair or replace damaged tissue. Students will examine these cellular mechanisms through primary research and case studies. They will also explore reprogramming technologies, such as induced pluripotent stem cells, alongside cell transplantation and tissue engineering.
Finally, students will design independent research projects to evaluate or propose regenerative strategies.
Dartmouth | Computational and Cognitive Neuroscience Lab, Department of Psychological and Brain Sciences
This research course explores decision-making from behavioural and neurobiological perspectives. Students will learn about methods used in psychology and neuroscience to study decisions at different levels.
These methods examine mental and cognitive processes, as well as the neural activity and mechanisms behind them. Ultimately, the course aims to broaden students’ perspectives on decision-making by deepening their understanding of brain function.
Dartmouth | Computational and Cognitive Neuroscience Lab, Department of Psychological and Brain Sciences
Neuroeconomics combines neuroscience, psychology, and economics to help explain how people make decisions. This emerging field uses advanced techniques to study how the brain processes information from different sources.
In this research course, students will explore economic and psychological theories of choice behaviour. They will also examine the mental and neural processes that influence decision-making.
Oxford | Department of Experimental Psychology
This research course explores how the human brain supports learning and decision-making. Students will discover key ideas from computational neuroscience, including reinforcement learning and Bayesian decision theory.
These concepts help explain the mechanisms behind our cognitive abilities. By combining insights from neuroscience, psychology, and computer science, students will develop a broader understanding of learning and decision-making. Overall, the course highlights how the brain, behaviour, and computational principles work together.
Oxford | Oxford Robotics Institute
Brain-computer interfaces have moved from science fiction into scientific and medical practice. These systems translate brain activity into digital commands, allowing users to control devices through neural signals.
In this course, students will explore the neuroscience and engineering behind this technology. They will learn how the brain supports movement, speech, and perception. They will also examine how researchers measure neural activity and turn those signals into actions.
The course also considers important ethical questions. Topics include privacy, human enhancement, and the changing relationship between people and machines. As a result, students interested in neuroscience, machine learning, and human-computer interaction will gain insight into this rapidly advancing field.
Cambridge | Department of Psychology
Motivation and emotion are important functions of the brain. They help individuals respond to their environment, support survival, and influence behaviour.
This research course introduces students to the psychological and neural foundations of emotion and motivation. Students will explore relevant research and theories while developing practical skills. These topics provide a foundation for understanding motivated behaviour and the mechanisms behind abnormal emotions and motivation.
Cambridge | Department of Psychology
This research course explores the foundations of pharmacology and the treatment of central nervous system disorders. Students will learn about the cellular and molecular processes involved in these conditions.
The course also introduces key concepts in cellular and molecular neuroscience, neuropharmacology, and behavioural neuroscience. Students will use this knowledge to examine neuropsychiatric disorders. Finally, they will explore the chemical causes of major central nervous system conditions and learn how drugs are used to treat them.
University of Toronto | Keenan Research Centre for Biomedical Sciences / St Michael’s Hospital
Why can the same event trigger excitement in one person, fear in another, and no reaction in someone else? This research course explores how perception, attention, memory, motivation, decision-making, and emotion shape human thought and behaviour.
Students will examine how emotions develop and influence cognition and relationships. They will also investigate what happens when psychological processes become disrupted.
Through research findings and clinical cases, students will explore conditions such as depression, bipolar disorder, schizophrenia, anxiety, PTSD, and anorexia nervosa. In addition, they will learn how these disorders are diagnosed and treated.
Harvard (Harvard Medical School) | Dettmer Lab, Department of Neurology
This research course explores brain anatomy, brain biology, and the degeneration associated with Parkinson’s disease (PD). Students will examine how these changes contribute to the main features of the condition.
The course also evaluates potential intervention strategies. Students will discuss the role of biomarkers in diagnosis and drug development. They will then explore how biomarkers could support earlier diagnosis and treatment.
Finally, students will consider new approaches to managing Parkinson’s disease. These may include combining different treatment strategies.
Carnegie Mellon | Robotics Institute
A robot depends on software to function effectively. This course introduces students to the engineering principles behind modern robotics. It focuses on the systems, tools, and workflows that make intelligent machines work.
Students will learn how to design, debug, and deploy software for complex robotic systems. Topics include Python, Linux, Git, ROS 2, simulation environments, and advanced robotics libraries.
Beyond hardware, the course explores how different components work together. Students will examine how sensors, control systems, machine learning, and motion work together reliably. This course is especially suitable for students seeking a practical, technically grounded introduction to robotics.
Harvard, Center for Astrophysics / NASA Jet Propulsion Laboratory (JPL)
This research course guides students through the spacecraft development process. Students will learn how to define scientific objectives, select an orbit, and design, test, and operate a spacecraft.
Along the way, they will explore propulsion, power, thermal control, structures, attitude and orbit control, and celestial mechanics. Students will also develop their own mission concept and investigate a spacecraft subsystem.
The course suits students interested in space research, astronomy, aerospace engineering, or mechanical engineering. It also offers an interactive learning environment. Students can share their ideas and contribute to class discussions throughout the course.
Harvard, Center for Astrophysics / NASA Jet Propulsion Laboratory (JPL)
This research course guides students through the spacecraft development process. They will learn how to define scientific objectives and select an orbit. Students will then explore how to design, test, and operate a spacecraft.
The course covers propulsion, power, thermal control, structures, attitude and orbit control, and celestial mechanics. Students will also develop their own mission concept and investigate a spacecraft subsystem.
This course is suitable for students interested in space research, astronomy, aerospace engineering, and mechanical engineering. It also encourages active participation, with students contributing ideas and responses to class discussions.
Oxford | Department of Engineering Science
This research course explores key engineering principles in thermofluids, aerodynamics, and experimental design. Students will develop theoretical knowledge and practical skills to address challenges in aerospace, energy, and sustainable technologies.
They will also learn how to apply these skills to real-world problems. The course encourages students to develop innovative solutions that support sustainability and net-zero goals. These applications span aerospace, sustainable energy, industrial systems, and related fields.
University College London
DNA molecules have unique chemical and physical properties. These properties allow researchers to use DNA for tasks beyond its natural function.
In this research course, students will explore the functional characteristics of DNA. They will learn how these properties can help create complex structures at the nanoscale. These structures can then perform customised tasks across different fields.
Applications range from biomedicine to manufacturing. Students will also explore the potential use of DNA nanostructures in data storage and complex chemical production.
Oxford | Department of Physics
This interdisciplinary research course combines microengineering, analytical chemistry, and robotics. It explores how miniaturised analytical systems and automated chemical processes can support new scientific applications.
Students will learn modern techniques in microfluidics and robotics. They will then explore how to apply these methods to real-world challenges in analytical chemistry and biomedical engineering.
UCL | Department of Computer Science
Biorobotics combines biology, biomedical engineering, computer science, and robotics. It explores how nature can inspire improvements in robotic intelligence, movement, and performance.
In this research course, students will discover bio-inspired ideas that have advanced modern robotics, particularly soft robotics. They will also explore the principles and methods used to design physically compliant robots.
Students will learn to use MATLAB and apply their knowledge in an independent research project on bio-inspired robotics.
Cambridge | Bio-Inspired Robotics Lab
This research course explores the connection between robotics and artificial intelligence. It focuses on machine learning techniques that support advances in modern robotics.
Students will begin with foundational concepts, including touch and interaction with the physical environment. They will then progress to more advanced methods.
These topics include reinforcement learning, learning from human demonstrations, and collaboration between multiple agents. Together, these approaches help students understand how robots can learn and interact with their surroundings.
Oxford | Department of Engineering Science
Soft robotics focuses on developing flexible, delicate, and safe robotic devices. These robots use soft actuators that mimic biological behaviour. As a result, they can interact with humans in ways that rigid robots cannot.
In practice, soft robots can perform tasks that would be difficult or dangerous for people. This research course introduces students to this emerging field.
Students will explore the concepts, development, and control of soft robots. They will also build a foundation for conducting their own independent research projects.
UC Berkeley | College of Engineering
This research course introduces students to the design and prototyping of mechanical systems that use microprocessors. These systems control machine activities, collect and analyse data, and interact with operators.
Students will complete laboratory exercises that explore different levels of software. They will also work with C and MATLAB. In addition, students will have the opportunity to use an Infineon PSOC6 microcontroller.
Oxford | Department of Engineering
This research course explores the fundamental principles of mechanics. It covers both statics and dynamics, including essential and advanced concepts.
Students will apply their knowledge through hands-on exercises, problem-solving sessions, and interactive simulations. These activities connect theoretical concepts to practical situations.
By the end of the course, students will understand the basics of mechanics. They will learn to analyse static equilibrium, assess structural members, and predict how particles and rigid bodies behave in dynamic situations.
Cambridge | Department of Medicine / Department of Engineering
Nanotechnology draws on physics, chemistry, biology, and engineering. It is a rapidly developing field that offers new solutions to industrial challenges.
In this research course, students will explore different aspects of nanotechnology and nanomaterials. They will also learn how these materials are used to create devices such as solar cells, superconductors, and medical sensors.
Cambridge | Department of Medicine / Department of Engineering
This research course explores the process of sensor data science. Students will learn about data collection, pre-processing, feature extraction, and machine learning modelling.
The course focuses on mobile and wearable sensors. Students will work with motion data, such as vibration, acceleration, and GPS. They will also explore physiological signals, including heart rate and skin temperature, as well as interaction data from app usage.
Next, students will learn basic digital signal processing and feature extraction techniques. They will also review basic machine learning methods. Finally, a mini-project will allow them to apply these skills to real-world sensor data science problems.
Cambridge | Department of Engineering
Wearable bioelectronics are changing how we monitor the human body. These technologies power devices ranging from smartwatches to advanced medical sensors.
In this course, students will explore the science behind these devices. They will then design an independent project based on a wearable bioelectronics application that interests them. Examples include cardiac monitoring and sleep-stage classification.
Through this work, students will develop a deeper understanding of wearable health technologies. They will also learn to apply engineering and data science to real-world challenges in biomedical engineering, neuroscience, and digital health.
Cambridge | Department of Engineering
This research course explores how advanced materials and technologies can shape the future of the built environment. It also examines how these innovations can support the global transition to a net-zero carbon society.
Students will investigate recent advances in materials and technologies that are transforming the construction industry. Through this work, they will develop the knowledge and skills needed to create sustainable infrastructure solutions.
The course also covers next-generation cementitious materials. Topics include low-carbon and alternative cements, self-healing composites, and circular material systems. Students will explore how these materials can improve resource efficiency by reusing construction and demolition waste.
Harvard | Department of Mathematics
What happens when information is no longer classical? This course introduces students to quantum information through its mathematical foundations.
Students will begin with familiar concepts from classical coding theory. They will then explore qubits, vector spaces, and the structures that emerge in quantum settings.
Next, the course introduces representation theory. Students will learn how it helps explain symmetry in quantum encoding. For those interested in mathematics, physics, or theoretical computer science, this course offers an opportunity to explore ideas at the forefront of modern science.
MIT | Department of Mathematics
Geometry is the study of shapes and plays a fundamental role in mathematics. It also helps us understand the world around us.
In this advanced research course, students will explore the beautiful and complex structures that define our universe. They will develop a strong foundation in modern differential geometry.
By the end of the course, students will be guided through the process of writing a paper that proves a geometric theorem. This experience will introduce them to the practice of conducting research in pure mathematics.
Oxford | Department of Computer Science
Quantum computing offers a new way to think about information, computation, and efficiency. This course introduces students to the mathematical foundations of the field.
Students will begin with core concepts from quantum mechanics. They will then explore how quantum information can be represented and manipulated using formal tools such as Dirac notation.
The course also introduces key ideas from computational complexity theory. Students will study major algorithms, including Grover’s algorithm, to understand how they work and why they matter.
This course is ideal for mathematically strong students interested in physics, computer science, and abstract reasoning. It provides a rigorous introduction to an important emerging field in modern science.
Stanford | Department of Mathematics
How can mathematics describe waves, planetary motion, quantum systems, and fluid flow? This course explores ordinary and partial differential equations. These equations help physicists understand change, motion, and structure.
Students will study both linear and nonlinear systems. Topics include Newtonian mechanics, the wave equation, the Schrödinger equation, and conservation laws in gas dynamics.
Although the course is proof-based, it also connects mathematics to physical phenomena. This approach helps students see how mathematical principles explain the world around them. The course is ideal for students seeking a challenging blend of mathematical precision and scientific application.
Cambridge | Faculty of Philosophy
This research course explores the relationship between mathematics and philosophy. Students will examine topics such as mathematical logic, set theory, and computability theory.
The course encourages students to pursue independent research. They will investigate fundamental questions in mathematics, logic, and philosophy. Through this process, students will gain a fresh perspective on mathematics and its connections to broader philosophical ideas.
Cambridge | Department of Computer Science and Technology
This research course is designed for students interested in computer science, mathematics, or related fields. It helps them build a strong mathematical foundation.
Mathematics is central to computer science and programming. It provides the tools needed to understand and analyse the algorithms and structures behind modern computing.
Students will explore essential concepts, including discrete mathematics, set theory, logic, probability, and algebra. These topics help explain both the theoretical foundations and practical applications of computer science.
Cambridge | Department of Computer Science and Technology
For centuries, people have explored how reasoning works and whether clear rules can govern it. The search for these rules helped shape mathematical logic and theoretical computer science.
This research course traces the history of these ideas, from Euclid’s axioms to the work of Frege, Peano, Russell, Gödel, and Turing. Students will explore formal systems, Gödel’s incompleteness theorems, recursive functions, and Turing machines.
The course also connects theory with practice. Students will investigate automated reasoning and interactive theorem proving. Through this work, they will learn about the potential and limitations of formal systems and how to apply these tools.
Cambridge | Department of Computer Science and Technology
Natural language processing (NLP) is a field of artificial intelligence that has advanced significantly in recent years. It supports applications such as virtual assistants, translation tools, and social media sentiment analysis.
In this research course, students will learn the fundamental techniques used to process language. These include morphological processing, parsing, and word sense disambiguation.
Students will also explore how these techniques work in real-world situations. This will help them understand the applications of NLP across different language-related tasks.
Cambridge | Department of Computer Science and Technology
Machine learning powers modern AI by enabling computers to learn from data without explicit programming. This research course introduces students to core machine learning (ML) principles and methods. It focuses on developing and evaluating models using sound scientific practices.
Students will gain hands-on experience with supervised learning algorithms and real-world datasets. They will also explore unsupervised learning and reinforcement learning.
Through these activities, students will learn to assess ML algorithms critically and understand their role in AI. They will also develop skills to apply rigorous methods to real-world challenges, including sentiment analysis.
Cambridge | Language Technology Lab
What is a language model actually “thinking” when it writes, reasons, or predicts what comes next? This research course explores how neural networks represent information and develop unexpected abilities.
Students will use tools such as n, m, and TransformerLens, along with Neuropedia, to study attention patterns and trace internal features. They will also investigate findings from cutting-edge interpretability research.
The course culminates in an independent research report based on hands-on experiments with real models. Basic Python experience is the only starting requirement. All other tools and techniques are introduced throughout the course.
Cambridge | Language Technology Lab
In 2018, a study examined three commercial facial-analysis systems. These systems correctly identified the gender of light-skinned men 99.2% of the time. However, they misidentified dark-skinned women 34.7% of the time. The companies had not noticed, tested for, or reported this gap before the study.
The systems were not designed to treat people differently. Instead, the disparity reflected earlier decisions, including which faces appeared in the training data.
This research course explores similar patterns in today’s dominant AI systems, including large language models (LLMs). Students will investigate how language, culture, gender, and identity can affect AI performance.
Basic Python familiarity is the only starting requirement. Evaluation methods, benchmarks, and experiment design are introduced throughout the course.
Cambridge | Language Technology Lab
What happens when an AI can remember, use tools, revise its plans, and interact with other AI systems? This research course goes beyond chatbots to explore autonomous AI agents and the behaviours they can produce.
Students will recreate a landmark experiment, build their own working agent in Python, and test how its behaviour changes under different conditions. These include limited memory, competition, and scarce resources.
The course culminates in an original research report and a live demonstration. Basic Python familiarity is the only starting requirement. All concepts related to agents, tools, and evaluation are introduced throughout the course.
Cambridge | School of Clinical Medicine
This research course focuses on end-to-end models for image classification and segmentation. Students will learn how machine learning architectures support these tasks.
Throughout the course, they will explore cutting-edge research in artificial intelligence, computer vision, and artificial neural networks. Finally, students will apply their knowledge in a hands-on assignment. This project will help them address real-world computer vision problems.
Oxford | Department of Engineering Science
This research course introduces deep learning techniques for computer vision and medical image analysis. Students will combine theoretical discussions with hands-on projects.
They will explore image classification, segmentation, object detection, and anomaly detection. Through these activities, students will learn how to design, train, and evaluate advanced models for different computer vision tasks.
Oxford | Department of Engineering Science
This research course explores recent advances in artificial intelligence. It focuses on foundation models and multimodal large language models (LLMs), including GPT, BERT, and DALL-E.
Students will examine how these models are built and trained. Key topics include self-supervised learning, attention mechanisms, and scaling laws. These concepts will help students understand the methods behind modern AI systems.
Oxford | Department of Engineering Science
What makes AI a useful teammate rather than an unreliable shortcut? This research course explores how people and AI can work together across different fields. These include medicine, education, business, engineering, and public services.
Students will investigate trust, automation bias, explainability, accountability, and human oversight. They will then design their own human–AI workflow.
By the end, students will understand how to combine AI’s speed and scale with human judgement, creativity, and responsibility.
Cambridge | School of Clinical Medicine
This research course introduces students to large language models (LLMs), such as GPT. Students will explore how machines understand and generate human-like text.
The course combines theory with practical exercises in natural language processing. It begins with an introduction to machine learning and neural networks. Students then progress to independent research projects supervised by faculty.
Along the way, they will explore advanced NLP techniques and consider the ethical implications and limitations of AI. The course aims to deepen their understanding of AI and encourage further study or careers in technology.
Cambridge | School of Clinical Medicine
AI can now write, interpret images, and generate content. But what happens when it begins to act? This course introduces students to the foundations of modern artificial intelligence.
Students will start with neural networks, computer vision, and language models. They will then explore autonomous AI agents and how these systems work. Topics include combining models, pursuing goals, using tools, making decisions, and operating independently.
The course also examines important challenges in AI, including bias, evaluation, and responsible deployment. It is ideal for students who want to understand not only how AI produces outputs, but also how it functions as an active system in the world.
University of California | School of Information
Smart spaces include intelligent homes, offices, and advanced urban environments. These spaces use connected devices to collect large amounts of video data. Examples include surveillance cameras, drones, and Internet of Things (IoT) sensors.
Making effective use of this data requires skills in data science, distributed systems, and video analytics. This course helps students develop these skills. They will learn to design, implement, and optimise systems for processing and analysing video data in smart spaces.
University of California | School of Information
This research course introduces students to data science through foundational principles and hands-on applications. It develops the skills they need to address real-world challenges.
Students will also explore large language models (LLMs), such as GPT, and their growing role in modern data science. Through practical projects, they will gain a comprehensive understanding of the data science pipeline. This includes data preparation, advanced machine learning, and AI integration.
Cambridge | Centre for Advanced Research and Education
Artificial intelligence (AI) and machine learning (ML) are transforming industries and driving innovation. Their applications span many fields, from healthcare and finance to environmental sustainability.
This research course explores how AI and ML address real-world challenges. Students will examine applications such as vaccine development, text mining for stock market prediction, and computer vision for autonomous robots. These examples demonstrate how the technologies can be applied across different industries.
Stanford, Media and Personality Lab | University of California, Santa Cruz, Department of Computational Media
Digital technologies and AI shape how people communicate, form relationships, access information, and engage with society. This research course explores how social media, digital platforms, and AI influence human behaviour, relationships, emotions, and society.
Students will use data science, machine learning, natural language processing, and social network analysis to identify patterns in real-world digital behaviour. By the end of the course, they will be equipped to investigate the human impact of emerging technologies. They will also explore the ethical challenges these technologies create.
Cambridge | Department of Applied Mathematics & Theoretical Physics
Climate change is one of the most significant threats facing humanity. It contributes to more frequent and intense environmental hazards, ecosystem degradation, and wider societal challenges.
This research course teaches students how to analyse climate change and environmental risks using machine learning. It combines scientific understanding with data-driven solutions.
Students will work with algorithms and datasets to apply their knowledge to pressing climate and environmental issues.
Oxford | Department of Engineering Science
Generative AI is rapidly transforming healthcare. Much of this progress comes from adapting general-purpose models into specialised clinical tools.
This course explores how AI is used in healthcare. Students will examine case studies of AI successes and failures in medicine. They will also consider ethical issues related to bias, safety, privacy, and accountability.
Next, each student will fine-tune and evaluate a small language model (LLM) for a healthcare use case of their choice. Examples include symptom triage, clinical summarisation, and mental health screening. Students will then assess how their changes affect the model’s behaviour.
Oxford | Department of Engineering Science
This research course explores how AI-based technologies are transforming healthcare. Students will learn about biomedical sensors, wearable systems, and the physiological processes behind them.
They will also learn to programme in Python or MATLAB. Using these skills, students will build their own AI pipeline from scratch using healthcare data.
Cambridge | Innovation Centre for Digital Molecular Technologies
This interdisciplinary research course explores how machine learning and artificial intelligence are advancing drug discovery and chemical development. Students will also examine emerging techniques for effective chemical and pharmaceutical synthesis.
The course combines chemistry, biology, chemical engineering, and computer science. Through this approach, students will develop the interdisciplinary knowledge needed to tackle cutting-edge challenges in these fields.
Cambridge | Department of Engineering
Virtual reality (VR) and mixed reality (MR) have significant potential to shape the future of technology. Their applications include training simulations, gaming, healthcare therapies, architectural visualisation, manufacturing, and design.
In this research course, students will explore these technologies and investigate their potential through research projects. They can choose from a range of topics, including VR simulations, tactile interface development, and psychophysical studies.
Oxford | Saïd Business School / Deep Learning Partnership
Scientific discovery has traditionally relied on human intuition, hypothesis formation, and experimental testing. This process can take decades to produce breakthroughs. This research course explores how artificial intelligence is changing scientific discovery. It introduces students to the growing role of computational science and machine learning.
Students will investigate how modern AI systems can generate new scientific hypotheses, design experiments, and identify patterns that researchers might overlook. The course covers three main themes: automated hypothesis generation using large language models and knowledge graphs, AI-driven experimental design, and algorithms that search complex parameter spaces more efficiently.
Oxford | Saïd Business School / Deep Learning Partnership
This research course introduces students to machine learning techniques designed for scientific applications. Topics include deep learning for time-series analysis, computer vision for microscopy, astrophysics and medical imaging, and large language models (LLMs) for literature mining, genome sequencing, and drug discovery.
Students will explore both supervised and unsupervised learning. These approaches help researchers identify patterns in labelled datasets and discover hidden structures in unlabelled data.
Harvard | The Institute for Quantitative Social Science (IQSS)
This research course introduces students to statistical methods, machine learning, and AI for addressing complex social issues. Topics include political polarisation, gerrymandering, and criminal justice.
Students will learn how these methods work and how to evaluate and apply them. Through hands-on projects with real-world datasets, they will also gain experience using tools such as GitHub and cloud computing.
The course covers several methods, including Ordinary Least Squares, Bayesian statistics, large language models, and survey methods. Students will learn to communicate their findings effectively to policymakers and the public.
Super Computer Center, MIT / UC San Diego / US Navy
Quantum computing could transform technology and science by solving problems that classical computers cannot. This research course introduces students to the principles of quantum computing, from superposition and entanglement to practical programming.
Students will gain hands-on experience using real quantum hardware through IBM Q and Qiskit. The course is designed for students from different academic backgrounds. No advanced knowledge of physics or mathematics is required. Instead, it uses visual learning, computer graphics, and real experimental data to explain quantum behaviour.
Cambridge | Department of Applied Mathematics and Theoretical Physics
This research course introduces students to quantum processes and their applications. It begins with the principles of quantum mechanics, including Dirac notation. Students will then explore how quantum states can carry information and how quantum teleportation connects to computation.
The course also covers qubits, quantum gates, and quantum cryptography, including quantum key distribution. Students will study key quantum algorithms, such as the Deutsch–Jozsa algorithm.
Previous knowledge of quantum physics is not required. However, a strong background in mathematics or physics would be beneficial.
Cambridge | Centre for Quantum Information and Foundations
Experiments at microscopic scales, such as the atomic scale, provide strong evidence for quantum physics. These discoveries have also led to many technological applications.
This research course explores the foundations of quantum physics. Students will examine quantum measurement and its relationship to general relativity. A strong background in mathematics or physics would help students get the most from the course.
Cambridge | Centre for Quantum Information and Foundations
General relativity (GR) is one of the two fundamental theories of physics, alongside quantum theory. It explains how space and time form a single entity called spacetime. The geometry of spacetime depends on the distribution of energy and mass, as described by Einstein’s equations.
In this research course, students will explore the theory of general relativity and its applications. Topics include curved spacetime, gravitational lensing, black holes, and gravitational waves. They will also examine important open questions in the field.
MIT | Kavli Institute for Astrophysics and Space Research
Astronomy is entering an era of big data. New facilities can observe more phenomena than humans can examine visually. As a result, astronomers must analyse millions of objects and vast amounts of data every day.
Machine learning and statistical methods help researchers classify, model, and characterise this information. In this research course, students will learn advanced machine learning techniques and apply them to real astronomical datasets. They will use these methods to discover patterns, build models, and deepen our understanding of the universe.
Stanford | Physics Department
Neutron stars and black holes are among the most remarkable objects in the universe. This research course explores the fundamental physics behind these extreme environments.
Students will learn the physical principles needed to understand the radiation these objects produce. Topics include classical electrodynamics, the motion of charged particles in electromagnetic fields, and the mechanisms that generate high-energy photons.
Students will also develop computer programmes and visualisations to simulate charged particles moving through the intense magnetic fields of neutron stars. This hands-on work will help them understand the physics behind some of the universe’s most extreme environments.
Oxford | Department of Physics
White dwarfs, neutron stars, and black holes are compact objects that form during the final stages of massive stars’ evolution. In this research course, students will explore the nature of these objects and their place in the history of the universe.
The course also covers topics in high-energy astrophysics. Students will learn about recent progress in detecting gravitational waves and discuss open questions in the scientific community. Finally, they will investigate how further studies of black holes, neutron stars, and white dwarfs can help scientists understand fundamental physics under extreme conditions.
Oxford | Department of Physics
This research course explores the structure and evolution of isolated stars and binary star systems. Students will examine the physical processes that govern how stars change over time.
Through theoretical concepts, observational data, and computational models, they will develop a deeper understanding of stellar evolution. In addition, students will take part in hands-on activities, computer simulations, and observational projects. These activities will reinforce their theoretical knowledge and help them build practical data analysis skills.
Oxford | Beecroft Institute for Particle Astrophysics and Cosmology
The standard model of cosmology suggests that around 85% of the matter in the universe is dark matter. This invisible substance interacts with ordinary matter mainly through gravity, making it difficult to study directly.
One major challenge in astrophysics is mapping dark matter using indirect observations. For example, scientists examine the arrangement of billions of galaxies captured by telescopes. They also study how dark matter’s gravity bends light.
In this research course, students will gain hands-on experience with advanced statistical techniques and machine learning. They will use methods similar to those employed by leading academic researchers to investigate dark matter and uncover its secrets.
University of Toronto | Canadian Institute for Theoretical Astrophysics
Plasma is a gas made up of charged particles. It accounts for over 90% of the visible universe and produces radiation from objects such as the Sun, black holes, and galaxies. Plasma also played a role in the early universe shortly after the Big Bang.
On Earth, plasma appears in many forms. Examples include nuclear fusion reactors, lightning, the aurora, lasers, televisions, neon lights, and fluorescent lights.
In this research course, students will explore how particles, electromagnetic fields, gravity, turbulence, and instabilities interact in plasma. They will also develop mathematical and computational tools to model plasma dynamics. These methods range from particle motion and Maxwell’s equations to magnetohydrodynamics. Finally, students will apply their knowledge to stars, black holes, fusion energy, and space weather.
University of Toronto | Canadian Institute for Theoretical Astrophysics
Black holes are among the most mysterious and extreme objects in the universe. According to the no-hair theorem, their defining properties are mass, spin, and charge.
Despite these simple properties, black holes produce some of the most complex and energetic phenomena in astrophysics. In this research course, students will explore what black holes are and how scientists study them.
Because black holes cannot be observed directly, researchers examine the radiation emitted by matter and plasma in their immediate surroundings. This approach helps scientists investigate these fascinating objects and understand the physical processes around them.
Cambridge | Institute of Astronomy
What makes a planet habitable, and how can astronomers search for life beyond Earth? In this research course, students will explore the techniques used to detect exoplanets and investigate their potential to support life.
They will learn how astronomers identify possible signs of biological activity, including specific molecules in planetary atmospheres. In addition, students will develop computational skills using Python and online exoplanet databases to analyse current planetary demographics.
These skills will support independent research projects. For example, students may identify promising habitable planets or study statistical trends among terrestrial (rocky), sub-Neptune, Neptune, and Jupiter-sized exoplanets.
Cambridge | Cavendish Laboratory / Trinity College
Few students get the chance to contribute to the discovery of a new planet. This research course offers that opportunity by introducing students to the methods astrophysicists use to detect, validate, and characterise exoplanets.
Students will work with real data from NASA’s TESS mission and follow-up observations from ground-based telescopes. Through this process, they will learn how to identify transit signals, distinguish them from false positives, and translate their findings into physical planetary properties.
Along the way, students will build practical skills in Python and data analysis. They will also gain a deeper understanding of how planetary systems form and evolve. For students interested in astronomy, astrophysics, and research, this course offers a unique opportunity to explore an active area of scientific discovery.
Cambridge | Faculty of Economics
Networks are all around us. From the architecture of financial systems, trade between companies and across countries, to the complex transportation system linking cities. This research course will explore how the events within the network interact and influence one another, and how can we represent, describe, or predict the events. We will emphasise a computational approach to social and economic network applications. Students will learn how to use Python to set and simulate network models; they will become familiar with the most recent research and techniques in network science and will develop excellent research skills.
Princeton | Niehaus Center for Globalization and Governance
In today’s data-driven world, proficiency in quantitative methods and data analysis is an essential skill for students interested in social sciences. Policymakers, scholars, and practitioners increasingly rely on empirical evidence to evaluate the effects of trade agreements, foreign investment, sanctions, and development interventions. Learning R—an open-source programming language widely used in academia and policy analysis—further strengthens these skills by enabling transparent, precise, and scalable data analysis. This research course offers a practical and accessible introduction to quantitative data analysis using R, with a focus on real-world applications in political science and economics.
Cambridge | St John’s College
What if the biggest forces shaping our world aren’t just laws or markets, but the invisible psychological shortcuts, social cues, and cultural influences guiding everyday decisions? Why do we take risks sometimes but avoid them at other times? How do our fears, biases, and need to belong drive everything from stock market crashes to the viral spread of fake news? Welcome to Behavioral Economics, where economics meets psychology, sociology, and neuroscience to unravel the mysteries of human behavior. This research course dives deep into how we perceive risk, make decisions, and are influenced by those around us. Students will also design and run their own experiment, collecting and analyzing real-world data to reveal behavioral insights on a topic of their choice.
Oxford, Institute for New Economic Thinking | Oxford Martin Programme on Systemic Resilience
Why do financial systems that appear stable suddenly collapse? This course introduces students to complexity economics, an emerging approach that treats the economy not as a system moving smoothly toward equilibrium, but as a network of interacting agents shaped by feedback loops, contagion, and systemic risk. Students will examine how small disturbances can spread through banking systems and markets, why traditional models often fail to capture fragility, and how modern economists use network theory, dynamical systems, and agent-based modelling to better understand crises. For students interested in economics, mathematics, finance, or public policy, the course offers a more realistic and intellectually ambitious framework for understanding how the global economy actually behaves.
Princeton | Niehaus Center for Globalization and Governance
This research course delves into the dynamic field of International Political Economy (IPE), exploring the complex ways in which international economic activities shape political relationships among states. It provides students with analytical frameworks needed to explore how trade, finance, and global production networks intersect with political power and decision-making.
Cambridge | Centre for Business Research
This research course introduces students to the study of political economy through the lens of the Cambridge tradition, which revives the field’s original interdisciplinary foundations in economics, philosophy, and politics. In contrast to contemporary mainstream economics, characterised by formal modelling, methodological individualism, and a de-ethicised scarcity framework, this research course approaches economics as a comprehensive social science grounded in realism, ontology, social theory, and ethics. It challenges students to rethink economic and policy questions from a bold standpoint, empowering them to uncover and interrogate the underlying structures, assumptions, and value commitments that shape economic life.
Oxford | Department of Primary Care Sciences
This research-intensive course serves as an exploration into the relationship between economics, mental health, addiction and substance use. We will discuss addiction and substance use through an economic lens, and students will be introduced to cutting-edge theories and models. Students will develop their research skills within health economics, particularly focusing on economic evaluations. With a spotlight on methodologies employed to assess the cost-effectiveness of healthcare interventions, students will engage in rigorous examination and measurement of health outcomes and cost valuation. They will also learn how to apply economic evaluations alongside clinical trials and employ decision-modelling techniques crucial for comprehensive research projects in mental health economics.
Oxford | Department of Primary Care Sciences
How do patients’ voices shape the future of healthcare? In this research course, you will discover the critical role of patient-reported outcomes (PROs)—with a special focus on health-related quality of life (HRQoL)—and learn how to measure and interpret these outcomes in real-world settings. As a key component of the research course, students will undertake their own independent research projects, applying their knowledge to design meaningful studies that assess quality of life outcomes in healthcare settings.
Oxford | Department of Primary Care Sciences
How do we know whether a health programme actually works and who benefits most? This research course shows students how to turn real-world health questions into rigorous evidence. By dissecting published studies, they will explore how researchers measure outcomes, control bias, analyze treatment effects, and draw policy conclusions. Students will then design and carry out their own reproducible research project, from choosing a dataset and developing a pre-analysis plan to testing results and writing a final paper.
Columbia | Columbia Population Research Center
Certain groups of individuals, including LGBTQ+, Hispanic/Latinx, Black/African American, Native Hawaiian/Pacific Islander, Native American/American Indian, are at greater risk of experiencing significant health challenges due to systemic inequities. This research course introduces students to Intersectionality and Population Health, two vital frameworks that help us examine and address these challenges. Each student will identify an intersectionality vulnerable population to study, design a research project, and propose a social justice intervention to address health inequities affecting that population. This action-oriented approach will equip students with both analytical and advocacy skills, bridging academic learning with meaningful community impact.
Columbia | Columbia Population Research Center
Why do some immigrants appear healthier than native-born populations despite facing greater social and economic barriers? This research course investigates the “immigrant health paradox” and asks whether it reflects a true health advantage or gaps in how health is measured across cultures. Students will examine how migration, discrimination, poverty, community support, and access to care shape well-being, then conduct an independent research project on a specific immigrant population and its implications for health equity and public policy.
Columbia | Department of Economics
To improve our understanding of the economic impact of the pandemic, this research course will introduce students to surveys of several contemporary policy issues in economic literature. Notably, we will discuss current economic and financial matters arising through and after the COVID-19 pandemic.
Columbia | Department of Economics
Climate change is one of the most pressing challenges of our time, with profound economic, social, and environmental implications. This research course explores the economic foundations of climate change, the role of markets and policies in addressing environmental challenges, and the transition towards sustainable development. Students will examine the economic drivers of climate change, including market failures, externalities, and public goods, and analyze policy solutions such as carbon pricing, cap-and-trade systems, and green subsidies.
Columbia | Department of Economics
AI is often described as a technological revolution, but its most far-reaching consequences may be economic. This course introduces students to the frameworks economists use to understand how AI is reshaping labour, markets, and power. Students will examine how AI changes the tasks that make up jobs, raising difficult questions about wages, skills, inequality, and who stands to benefit from technological change. The course also explores how data and scale allow a small number of firms to dominate AI-driven markets, with implications for competition and opportunity. Bringing these ideas into the policy arena, students will engage debates around regulation, taxation, and how governments should respond to rapid technological transformation. For students interested in economics, public policy, or the future of work, this course offers a timely and analytical way to understand one of the defining changes of our era.
LSE | International Inequalities Institute
What is inequality, and how is it best measured and tracked over time? How do people experience inequality? Inequality is an important and complex issue that manifests in people’s lives, national politics, public policies, and economic systems. Its scientific study draws on multiple disciplines, including economics, sociology, and development studies. This research course will examine key perspectives on inequality, sociology, and development studies.
Harvard University | The Center for Labor and a Just Economy (CLJE)
This research course delves into the multidisciplinary study of skilled immigration, combining economics, policy analysis, and case studies.This research course offers a comprehensive exploration of skilled immigration economics, bridging the gap between research and policy. By completion, participants will be equipped with a solid foundation in the field, enabling them to critically analyse and actively contribute to ongoing discussions regarding skilled immigration and its economic impact.
Yale | MacMillan Center for International and Area Studies
Cities are often treated as neutral spaces, but they are anything but neutral. This course teaches students how to read the built environment as a record of power, memory, exclusion, and everyday life. Drawing on architecture, urban studies, heritage studies, and critical theory, students will explore how cities preserve certain histories while erasing others, and how official narratives often differ from the lived realities embedded in place. A major part of the course involves developing an original research project focused on a city or site meaningful to the student. For students interested in history, urbanism, postcolonial thought, or cultural analysis, it offers a rich and highly original way of thinking about space.
Brown | Watson Institute for International and Public Affairs
How does a society learn to see another group as “the enemy”—and what happens when war enters everyday life? This research course explores how language, media, religion, memory, race, gender, and visual culture shape the divide between “us” and “them.” Through global case studies, students will investigate how conflict is lived, remembered, and imagined, from monuments and propaganda to nuclear anxiety, drones, video games, and the changing future of warfare.
Cambridge | Department of Sociology
This research course introduces students to the study of race and racism as dynamic social, historical, and political phenomena. Through interactive sessions, students will explore how race is constructed, institutionalised, and contested across various contexts and time periods. The course critically engages with how policies in education, housing, health, immigration, and criminal justice contribute to racial inequality, while also examining global governance and international development through a racial lens.
Cambridge | Department of Sociology
This research course aims to cultivate critical thinking and provide a comprehensive understanding of contemporary global development issues. Topics we will discuss include, Millennium and Sustainable Development Goals, development traps, pandemic and post-pandemic challenges, urbanisation and gentrification, development theory, international and regional co‑operation for development, bottom-up perspective, decolonial studies, development and intersectionality, and corruption, among others.
Yale | Department of Political Science
Political psychology seminars often focus on American political behavior, while comparative politics rarely address psychological perspectives directly. This research seminar bridges that gap by exploring how psychological factors intersect with comparative political systems, shaping attitudes and behaviors across diverse contexts. The research course examines how political beliefs are formed, revised, and expressed through action, emphasizing the influence of personality traits, cognitive processes, and identity—both individual and collective—on political engagement.
Yale | Department of Political Science
AI is no longer just a tech story. It is a political game-changer transforming power, governance, and global rivalries. From Big Brother surveillance states to digital propaganda machines, AI technologies are rewriting the rules of control, democracy, and international competition. In this research course, students will dive into how AI reshapes political systems worldwide. Students will design and carry out their own original research projects—whether mapping the global spread of AI surveillance, measuring misinformation fueled by large language models, or comparing national AI policies and their impact on governance.
UPenn | Annenberg School of Communication
This research course will explore and clarify this tension by reviewing many decades of research and philosophy into the function of propaganda, disinformation, and the social role of mass media. Students will gain a greater understanding of how power operates through the media (including traditional modes of media and social media) and learn how to apply these insights to real political media environments that are relevant to the current moment. In addition to the history of mass communications research, students in this research course will be introduced to important concepts from narrative theory, rhetoric, affect theory (the study of emotions), and political psychology. We will learn how to apply these ideas to real-world social and political contexts.
Harvard | Department of Anthropology
What can a photograph or film reveal that words alone cannot? This course explores visual media as a way of studying politics, society, identity, and power. Through film, photography, and ethnographic methods, students will learn how images construct meaning, how representation shapes understanding, and how visual storytelling can uncover social realities that might otherwise remain hidden. In the second half of the course, students will design their own independent project, whether as a visual essay, short ethnographic film, or research paper combining theory and visual analysis. This course is an excellent fit for students who want to combine creativity with serious academic inquiry into media, culture, and social life.
Cambridge | Department of SociologyCambridge, Department of Sociology
Technological advancements may seem purely scientific and technical, devoid of politics and social relations. However, no technological invention exists in a vacuum, and all inventions are entangled in sociopolitics. This research course will explore how AI changes and disrupts our lives, how society shapes AI and how AI shapes society in return, as well as which inequalities are mitigated and which ones are reproduced through the integration of this technology into our lives. How AI impacts one’s life is also moulded by the social categories individuals belong to, including but not limited to their gender, ‘race’, class, sexuality; the intersection of which will also be addressed in the course.
Cambridge | Department of Sociology
Spanning across both physical and mental health and borrowing primarily from sociology of health and illness and gender, students taking this research course will develop a critical understanding of the main themes and debates in these fields. By the end of the research course, students will have completed a research paper, which will cut across several themes in health and gender according to their personal research interests.
Cambridge, Institute for Global Prosperity / UCL, Institute for Global Prosperity
How do ideas about “men” and “women,” masculinity and femininity, or homosexuality and heterosexuality shape our experiences and desires? To what extent are our identities and sexualities formed by social expectations, and how do people resist or conform to these norms? This research course challenges students to think critically about gender and sexuality as socially constructed and deeply political. Students will explore key social scientific theories and engage with diverse global perspectives, examining gendered identities and sexual norms across cultures from Africa to Asia and the Middle East. Foundational feminist and queer theories meet anthropology, sociology, and philosophy to reveal how bodies, habits, and performances shape—and are shaped by—compulsory norms like heteronormativity.
Oxford | Faculty of Classics
Why are languages so different – and thus so hard to learn?
We will explore the social relevance of language and the results
of language contact. Students will conduct independent
research by constructing linguistic data, analysing big data
and performing context-oriented keyword analysis.
Students will investigate how language develops, interacts,
and how to what extent we can manipulate our patterns of
language usage for specific purposes.
UPenn | Annenberg School of Communication
As so many dynamics of the social world are increasingly being imprinted into widely available datasets, the ability to harness and derive insights from large text corpora is increasingly being valued in the worlds of business, academia, and non-profit organizations. How can we make sense of the vast amounts of information available online, and how can we relate it to the social context in which it appears? This research course introduces basic tools for retrieving and analyzing unstructured text data. Students will learn i) how to scrape and pre-process messy text datasets, ii) a variety of cutting-edge approaches to supervised and unsupervised analysis of text data, iii) best practices for validating automated inferences against a human-labeled dataset.
Columbia | Department of Architecture
This research course explores the intersection of architecture with social, political, and environmental concerns, prompting critical inquiry into the discipline’s role in addressing contemporary challenges. Students examine debates and arguments surrounding architecture’s engagement with societal issues and its environmental impact. Through case studies spanning recent decades, topics such as aesthetics, sustainability, spatial organisation, and cultural contexts are explored. Emphasis is placed on developing a nuanced understanding of architecture’s role in addressing pressing issues while maintaining fidelity to its unique principles. The course fosters critical thinking and encourages students to navigate the complexities of architectural discourse within broader societal contexts.
Columbia | Department of Architecture
This research course will examine the core topics in architectural thinking by introducing students to critical arguments and debates in the discipline’s contemporary discourse. Covering approximately the last 30 years, we will look at architectural projects, buildings, material configurations, construction systems, and organisational models along with a series of theoretical and historical frameworks relevant to them. Topics include representation, programme, spatial organisation, context, whole, element, content, referent, the digital, aesthetics, phenomenology, evolving notions of sustainability, and developing cultures of reuse and renovation.
Columbia, School of Business | Geico, Head of Marketing
In today’s ultra-competitive business world, effective Marketing Management and Brand Strategy are key components for any business to achieve success. However, these are not easy tasks, especially given that modern-day consumers are constantly overwhelmed with information. This research course introduces the principles of brand management and advertising as practised by industry leaders today. This research course is relevant for students interested in driving consumer demand regardless of career path.
Cambridge | Judge Business School
Why do some start-ups receive a valuation of several billion
dollars, while others cannot even raise the amount to get by
and survive? Why do only a handful of start-ups go public?
The research course will focus on entrepreneurial finance,
i.e. venture capital investment. This research course exposes students to the core theories, concepts, and tools used to
screen high-potential start-ups and maximize the return on
investment. Students will learn key theoretical concepts,
tools, and approaches to entrepreneurial finance and their
application in valuation and investment in new businesses.
Cambridge | Judge Business School
This research course delves into the dynamic landscape of entrepreneurship in the age of AI and complementary digital technologies. It will explore the fundamental principles of entrepreneurship, including identifying opportunities, developing innovative business models, and securing funding. Students will explore the eminent challenges and opportunities presented by the rapid advancement of generative AI and digital technologies. By the end of the course, students will gain practical experience and develop the academic skills necessary to conduct rigorous academic research at the intersection of entrepreneurship and disruptive digital technologies.
Imperial College | Department of Economics & Public Policy
Why do some businesses dominate their markets while others struggle to survive? This research course explores the economic forces behind pricing, competition, strategy, and growth. Students will examine how supply and demand, market structure, game theory, government policy, inflation, and interest rates shape the decisions firms make. Key topics include supply and demand dynamics, market structures, pricing strategies, game theory, and the role of government intervention. The research course also examines macroeconomic factors such as inflation, interest rates, and economic growth, enabling students to assess how broader economic trends influence industries and global markets.
Australian National University | Centre for Applied Macroeconomic Analysis (CAMA)
What drives stock prices? This research course covers the basics of stock market dynamics. Students will grasp fundamental concepts in finance and economics, and specifically, learn to forecast economic and financial data using statistics and economic models. Real-world case studies, simulations, and practical exercises will be integrated to provide hands-on experience in applying modelling techniques and investment strategies to actual financial data. By the end of this research course, students will be equipped to make informed investment decisions and manage financial risk adeptly in today’s dynamic financial markets.
Oxford | Hertford College
The concept of money itself is often not well understood. Terms such as “printing money”, “money debasement”, “fiat money”, “quantitative easing” and “intrinsic value” are often misunderstood. This research course explores how money, banks, and financial markets shape economies—and why their failures can trigger global crises. Students will examine inflation, central banking, money creation, debt, equity, bond markets, exchange rates, and international financial flows. By the end of the course, they will be equipped to analyze monetary policy, understand financial instability, and investigate the forces driving the global economy.
Columbia | Industrial Engineering and Operations Research
In today’s complex financial environment, achieving financial literacy is not just beneficial—it’s imperative. Whether you’re aspiring to a career in finance, managing personal or family investments, or supervising a wealth management firm, a good understanding of financial markets and products is essential. This encompasses familiarity with various asset classes such as foreign exchange, equities, bonds, and commodities and different valuation methods, interrelationships, and the strategies employed to construct portfolios that balance risk and return effectively. The objective of this research course is to equip students with practical knowledge and a solid understanding of the major areas within finance.
Oxford | Saïd Business School
Space is no longer just the domain of superpowers and national space agencies. It is now a fast-moving arena where startups, major firms, and governments compete to shape new technologies, markets, and systems of governance. This course uses the emerging space economy as a lens for understanding how innovation works in strategic industries. Students will examine how new ventures identify opportunities, how public policy and funding shape technological development, and how geopolitics influences everything from satellite infrastructure to spectrum and data policy. For students interested in business, entrepreneurship, technology, and public policy, the course offers a timely and analytically rich introduction to one of the most dynamic sectors in the world.
LSE | Department of Management
This research course aims to balance theory and practical application by focusing on issues that will help students understand how to influence the attitudes, behaviour, and success of people in contemporary organisations (includ- ing leaders themselves). Topics covered in this course include the individual in the organisation, motivation, the multicultural workplace, decision-making, and effective leadership. The ability to understand, motivate, and people is key to becoming an effective manager in any industry or sector.
LSE | Department of Management
Why do people follow an AI recommendation even when it may be wrong? This research course explores how artificial intelligence changes the way people think, choose, and behave. Drawing on psychology, behavioural economics, and organisational research, students will examine cognitive bias, trust in AI, automation bias, nudges, misinformation, social influence, and human–AI collaboration. Through cases from business, healthcare, education, public policy, and social media, they will investigate when AI improves judgement, when it distorts it, and why human behaviour remains central to every AI-assisted decision.
LSE | Department of Management
When should we trust an AI to make a decision and who is responsible when it gets one wrong? This research course explores how people and organisations make choices under pressure, uncertainty, and incomplete information, and how AI is changing that process. Through cases from medicine, law, finance, business, and government, students will examine bias, intuition, expertise, automation, and accountability, ultimately asking where human judgement still matters most. The course concludes by considering the future of human expertise and judgement in an increasingly AI-driven society. No technical or programming knowledge is required.
LSE | Department of Management
What happens when AI begins to influence who gets hired, how employees are evaluated, and even how their work is monitored? This research course examines how artificial intelligence is reshaping leadership, teamwork, job design, recruitment, workplace culture, and employee well-being. Using case studies from healthcare, finance, retail, education, and technology, students will explore algorithmic management, workplace surveillance, digital inequality, bias, trust, and accountability. Rather than asking only whether AI will replace workers, the course investigates how it is changing power, relationships, and decision-making inside modern organisations.
LSE | Department of Management
In this research course, students learn to question and apply sociological or psychological theories to understand inequalities in organisations. The course particularly helps students to understand why women don’t progress at the same pace as men at work. The course specifically looks at gender and stereotypes attached to the gender within a society and how this transpires to the workplaces. It also extends to other identities that might equally explain the reasons for inequalities within workplaces. By studying this course and working on their independent research projects, students will develop hands-on research skills and also understand the interdisciplinary process of applying theories from different fields in solving complex problems.
LSE | Department of Management
This research course focuses on organisational behaviour, aiming to understand how individuals’ actions impact organisational success. Through case studies and discussions, students explore the dynamics that shape behaviour within startups, social enterprises, and other organisations. The course delves into psychological and sociological perspectives, examining how cultural factors influence decision-making and behaviour, particularly in global contexts. Students conduct independent research projects to gain insights into real-world scenarios and develop a comprehensive understanding of organisational dynamics and effectiveness.
Cambridge | Centre for Advanced Research and Education
The first ever AI conference was held in 1956. Why did it take half a century for technologies to become ubiquitous in our lives? This research course is designed for aspiring entrepreneurs, innovators, and investors that are fascinated by the interaction of multiple areas, like science, technology, finance, and economics. From the basics of finance and startup economics to assessing technological feasibility and market fit, this research course provides an comprehensive introduction to the entrepreneurial and venture capital world.
Stanford | Center for International Security and Cooperation
The history of nuclear weapons did not begin and end with Oppenheimer. This course examines how nuclear weapons reshaped international politics after 1945 and how states and institutions have attempted to control, limit, and eliminate them ever since. Students will study the development of deterrence theory, the expansion of nuclear-armed states, and the major treaties and initiatives that have defined global non-proliferation and arms control efforts. The course also addresses contemporary challenges, including nuclear terrorism, regional rivalries, and the impact of emerging technologies on strategic stability. It is an excellent choice for students interested in international relations, security studies, history, and diplomacy.
Cambridge | Department of Politics and International Studies
The key question of this research course is: ‘How to maintain stability and order in a world that seems to be changing at an ever increasing pace?’ Students will be introduced to the fundamentals of Europe post-World War II order, the foundations of post-1991 US hegemony, the rise and growing integration of China in the global economy, aspects of revisionism by Russia, and the geostrategic challenges of growing multipolarity.
Cambridge | Department of Politics and International Studies
Students will be introduced into key texts on the causes of war, including material from psychology, evolutionary biology, archaeology, history, social anthropology, and international relations. The course will furthermore draw on a selected range of cases from mythology, history, and current instances of warfare in order to illustrate some of the most cogent hypotheses. It will also explore the purpose and rationality of warfare, be it for territorial expansion, economic gain, for religious faith, or for collective identity. Last not least, the course aims to assess possibilities of preventing, containing, or regulating war as a system of organised violence by means of legal and ethical norms as well as strategies of conflict-resolution.
Cornell | Department of Government
What is life good for? This course takes students into some of the deepest and most enduring questions in philosophy, political thought, and the study of human nature. Drawing on existentialism while developing the lens of political existentialism, the course explores themes such as identity, freedom, anxiety, morality, truth, religion, alienation, love, and hope. Rather than treating these as purely abstract questions, it asks what they reveal about the individual and about society. Highly interdisciplinary and intellectually ambitious, this course is ideal for students who want to think seriously about meaning, selfhood, and the political implications of being human.
UCLA | Department of Sociology
Students will be able to analyse the world in ways that transcend binaries between nature (natural sciences) and society (social sciences), particularly in relation to real-world issues like climate, environmental sustainability, transitions, health inequality, and environmental justice. Engaged students will obtain a nuanced and diverse set of analytical tools to assist in understanding how “the environment” and environmental matters cannot be understood outside of and apart from the social world, and how the social world is deeply intertwined and embedded within “the environment.”
Oxford | Faculty of Classics
Making one’s voice heard in public was a sought-after skill
for those at the heart of the Athenian democracy, the Roman
republic and later the Roman empire. The skilful use of
language was a critical tool and a powerful weapon. We will
focus from the orators of the Athenian democracy to the
politicians of the Roman republic. Students will develop an
independent research project on political rhetoric, ancient
history or relevant areas in the context of its time and
discourse.
Cambridge/Brandeis/NYU | Center for Middle East Studies
This interdisciplinary research course explores how artificial intelligence and algorithmic systems are reshaping culture, identity, and global power structures. The research course begins by introducing students to foundational concepts in cultural studies, including key debates around music, art, nationalism, postcolonialism, race, and gender. Building on this groundwork, students then examine how digital cultural practices, such as social media, automated decision-making, and generative AI, are transforming societies and economies. Through readings, multimedia case studies, and critical discussions, students will analyze how algorithmic systems both reflect and reproduce cultural norms, and how they may reinforce or challenge existing social hierarchies.
University of Chicago | Booth School of Business
There is a significant contemporary debate on how the state should interact with the individual, especially in the context of respecting the individual’s concepts of norms, privacy, and history. Students will conduct their independent research project throughout the research course, which will enable them to explore and delve into the central questions surrounding law, economics, and political philosophy.
Cambridge | Faculty of Philosophy
The recent development of artificial intelligence has raised important questions about society, ethics, the mind, and language—for computer scientists, tech companies, and policymakers alike. These concerns all lead to a central question: how can we build a safer, more equitable future shaped by AI?
This research course is designed to help students explore the complex issues surrounding artificial intelligence. By engaging with philosophical frameworks and theories, students will examine AI from a multidimensional perspective, equipping them with critical tools to reflect on its ethical, social, and conceptual implications—whether they aspire to become policymakers, computer scientists, or scholars in the future.
Yale | MacMillan Center for International & Area Studies
Can we reconcile the state-centered origins of human rights with the emergence of transnational corporations as human rights violators? Can human rights still justify humanitarian intervention in the context of armed conflicts? How to uphold human rights when other public interests are at stake, such as national security? This research course explores both the ideas behind human rights and the international laws designed to protect them. Students will examine how rights are defined, enforced, and challenged through cases involving gender, migration, development, multinational corporations, armed conflict, and national security. Drawing on law, political theory, sociology, and international relations, the course asks whether today’s human rights system can keep pace with a rapidly changing world.
Yale | MacMillan Center for International & Area Studies
Who has the right to cross a border, and who gets to decide? This course examines migration law as a window into some of the most fundamental questions in modern political life: sovereignty, citizenship, rights, exclusion, and belonging. Drawing on law, political theory, sociology, and international relations, students will investigate how states regulate migration and how legal categories shape the condition of migrants within and across borders. The course also addresses issues such as border policing, counter-terrorism measures, and the human rights of migrants, encouraging students to think critically about what migration law reveals about constitutional states themselves. It is especially well suited to students interested in law, public policy, and global affairs.
Harvard | Afro-Latin American Research Institute
How powerful is the written word of law? This course examines the U.S. Constitution not simply as a founding text, but as a site of ongoing conflict over freedom, equality, and belonging. Students will study landmark cases on race, education, immigration, and gender while engaging major interpretive frameworks in legal studies, from originalism to intersectionality. Rather than treating law as static, the course asks how legal language shapes lived realities and why rights on paper do not always translate into justice in practice. It is especially suited to students interested in law, political theory, and the social life of institutions.
Oxford | Faculty of Classics
What did it mean to be sick before modern hospitals, laboratories, and medical technology? This research course explores how people in the ancient Mediterranean understood the body, explained illness, and pursued healing through observation, diet, drugs, surgery, physical therapy, and religious ritual. Students will examine the rise of anatomy and systematic medical inquiry alongside questions of mental illness, disability, sexuality, epidemics, death, and access to care. By comparing ancient practices with modern medicine, they will uncover both the origins of healthcare and the ideas that still shape it today.
Oxford | Faculty of Classics
What is consciousness, and how can we understand and study it through the interdisciplinary lenses of cognitive science, philosophy, and artificial intelligence? This research course explores the science of the mind and consciousness through the interdisciplinary lenses of cognitive psychology, neuroscience, philosophy, and artificial intelligence. Students will engage with core theories, landmark experiments, and key debates that define the field. Balancing theoretical depth with accessibility, this course invites students to think about cognitive science.
Harvard | Lakshmi Mittal and Family South Asia Institute
Was colonialism good for the world, or did it make life worse for people who lived under it? This is a live debate among people who are still trying to come to terms with their colonial pasts. This research course probes such questions by examining the British Empire during the 19th and 20th centuries, its means of expansion, economic incentives, and its racial assumptions. The course explores special topics relating to the imperial legacy. These include trade in cotton, opium and tea; colonial wars fought in Afghanistan and China, and anti-colonial movements, such as the one led by Gandhi, in the twentieth century. We also discuss violence, the drawing of borders, emigration, and refugees. The case studies of Israel-Palestine and India-Pakistan will factor prominently.
Oxford | Nissan Institute of Japanese Studies
This research course will allow students to investigate different feminisms that have been employed by feminists across East Asia in the 20th Century and up until the present day. The course will broadly focus on constructions of femininity, masculinity, non-binary, and other identities in Japan, Korea, and China. Additionally, it will allow students flexibility to explore other areas in the region and take a transnational approach to historical work. We will also look at how these identities and the disparities between them contributed to the emergence of many transformed into many different feminist movements across and between places in this region. These feminisms will include formal protest movements, literary movements, grassroots organisations, and more subtle cultural critiques of gender normativity.
Cambridge/Brandeis/NYU | Center for Middle East Studies
Through integrating diverse bodies of scholarship—including gender theory, decolonial and postcolonial studies, queer theory, and human rights frameworks from legal and policy perspectives—the course provides an interdisciplinary approach to the study of human rights deeply rooted in questions of gender. Students will engage with seminal works by scholars such as CLR James, Sylvia Wynter, Gayatri Spivak, Michel Rolph Trouillot, Ratna Kapur, Hannah Arendt, Audra Simpson, Walter Mignolo, Giorgio Agamben, Judith Butler, Lila Abu-Lughod, and Wendy Brown, among others. Alongside these theoretical perspectives, students will analyze the evolution and application of international legal frameworks aimed at securing the rights of women and other marginalized groups.
Cambridge / Brandeis / NYU | Center for Middle East Studies
Does anyone deserve to be unfree? What does captivity tell us about freedom? This research course tracks the history of captivity, prison, and incarceration. We examine laws and literatures of captivity in ancient Rome and the mediaeval Islamic world through to humanitarian debates around slavery and modern prisons and the political economy of successive wars on Crime, Poverty, Drugs, and Terror in the Americas. Our protagonists range from anti-colonial nationalists in Kenya and Chinese indentured labourers, to prisoners of the Russo-Ottoman wars and convict labourers in Australia.
Cambridge / Brandeis / NYU | Center for Middle East Studies
In 1967, Roland Barthes famously wrote on “the death of the author”. What he was referring to was the fact that the authorial voice is almost impossible to recover underneath the textual layers of literary works. Put differently, he wanted to separate the work from the author and let the work speak for itself. Did Shakespeare believe in witches (cf. Macbeth) or did Orwell worry about the decline of the English language (cf. Newspeak in 1984)?
This research course revisits the question of the authorial voice in the age of AI. It addresses the fundamental questions of present-day discourse: What is creativity? How are authors distinctive? Why do we write?
Cambridge, Trinity College | Faculty of Asian and Middle East Studies
How do children acquire language so rapidly? How do sounds become words, and words become meaningful sentences? Why do the world’s languages differ so dramatically while sharing many underlying similarities? And what can language reveal about the human mind, cognition, and society? This research course explores how linguists investigate these questions through the systematic analysis of empirical evidence. Students will gain a broad understanding of contemporary linguistics while developing the analytical skills needed to approach language as scientists.
UCLA | Herb Alpert School of Music
Since ancient times in humankind history, sound, music and health have been intertwined. People around the world have realised and experienced the health-enhancing effects of sound and music. Traditional music therapy uses music to support healing and improve well-being, addressing various physical, emotional, and cognitive needs. Therapists employ music elements to aid in communication, reduce stress, and enhance overall quality of life, often in healthcare or therapeutic settings. This course studies how different cultures use sound and music in healing rituals around the world.
UCLA | Herb Alpert School of Music
This interdisciplinary research course delves into the profound influence of popular music on identities throughout history, examining diverse musical traditions from Africa, Europe, Asia, America, and Oceania. Through hands-on activities and participatory exercises, students explore the social, cultural, and historical contexts of popular music, transcending genre and geography. Through readings, discussions, and research projects, students develop critical thinking skills and deepen their understanding of how popular music influences society and identity. All students, regardless of music experience, are welcome to participate in this inclusive exploration of global popular music.
Princeton | Seeger Center for Hellenic Studies
This research course explores the dynamic relationship between art and colonialism in the Mediterranean, from antiquity to the modern day. It offers a comprehensive examination of how diverse colonial powers have influenced and shaped the rich tapestry of cultural production within the region. Employing a multidisciplinary approach, the course blends art history, cultural studies, and historical analysis to unravel the nuanced complexities of artistic expression within the intricate web of colonisation.
Princeton | Seeger Center for Hellenic Studies
What makes images so powerful? Why do they move, persuade, and shape people across cultures and centuries? In a world flooded with everything from sacred icons to viral memes, this research course explores the global history of visual language and the forces that give images their lasting impact. Students will investigate what an image really is, tracing ideas from ancient Asian and Mediterranean philosophies to medieval theology, early modern debates, postcolonial theory, and today’s digital culture. This course covers religious icons, political propaganda, aesthetic forms, and new media, using case studies from Asia, Africa, Europe, and the Americas.
Cornell | Cornell Center for Historical Keyboards
This interdisciplinary research course investigates the intersections of gender, musical subcultures, and artistic innovation through the lens of extraordinary contributions to musical history—focusing primarily on women, but also including overlooked creators and practices beyond the traditional Western canon. Centered on piano culture and its surrounding subcultural spaces, the course draws from gender studies, historical performance practices, and embodied inquiry to explore how diverse figures have shaped, preserved, and transformed musical heritage in ways both visible and marginalized.
Admissions
How to Apply (Early/Regular Admissions to Fall 2026 Cohort)
Step 1
Read Future Scholar Prospectus
Read the Future Scholar Prospectus to learn about the programme. You can also attend an information session to find out more.
Step 2
Create Account on CCIR Admissions Portal
Submit Application
Create an account on the CCIR Admissions Portal and submit your application. Then, choose from the research courses offered in the current round.
For the spring round, submit your application before the Early Admissions Deadline of October 1, 2026, or Regular Admissions Deadline of October 15, 2026.
Step 3
Academic Interview
Outstanding applicants will be shortlisted for an Academic Interview. If selected, the scheduling team will arrange an interview with the applicant. Interviewers are typically PhD candidates from Cambridge, Oxford, or Harvard.
During the 15–30-minute interview, we’ll assess your academic background and interests. We’ll also explore how you approach problems in your chosen field.
You will receive a decision on your interview invitation within one week of submitting your application.
Step 4
Official Offer
Applicants who receive a conditional offer will undergo a final admissions review. Professors teaching their selected courses will assess their applications and interview performance before reviewing applicants from the Early and Regular Admissions pools.
Successful applicants will then receive an Official Offer.
The decision on the Official Offer will be made within 1–2 weeks after the applicant submits their research course selection.
Tuition is expected to be paid in full within 5 business days of receiving the Official Offer. This payment confirms enrolment.
How to Apply (Pre-Application to Spring 2027 Cohort)
Step 1
Read Future Scholar Prospectus
Attend Information Session
Step 2
Create Account on CCIR Admissions Portal
Submit Application
Select research areas of interest.
Submit your Fall pre-application before the Pre-Application Admissions Deadline of January 15, 2027.
Step 3
Academic Interview
Outstanding applicants will be shortlisted for an Academic Interview.
If selected, the scheduling team will contact the applicant to arrange the time with an interviewer, typically PhD candidates from Cambridge, Oxford, or Harvard.
During the 15 to 30 minute interview, we’ll assess your background, interests, and your ability to think through problems in your field.
The Academic Interview invitation decision will be made within 1–2 weeks after application submission.
Step 4
Conditional Offer
A conditional offer to the programme will be extended to applicants who demonstrate strong academic preparation and perform exceptionally in the Academic Interview.
The decision on the conditional offer will be made within 1–2 weeks after the Academic Interview.
A refundable deposit of 500 GBP / 600 USD is required to confirm the seat.
Step 5
Select Research Course on January 15, 2027
Conditional offer holders will receive an invite to register their research course preference on January 15. Applicants will be asked to submit their research course within 10 business days.
Step 6
Official Offer
The applications and interview of the conditional offer holders will receive a final admissions evaluation from the professors teaching their selected courses, before the professor starts reviewing Early and Regular Admissions pool applicants.
Successful students will then be extended an Official Offer.
The decision on the official offer will be made within 1-3 weeks after the applicant’s research course selection is submitted.
The remaining tuition is expected to be complete in full within 5 business days after receiving the official offer as a confirmation of enrollment.
Admission Deadlines & Start Dates
(2026-2027)
SPRING
SUMMER
FALL
Pre-Application Opens
9 Aug
15 Jan
1 Apr
Official Admission Opens (Pre-Application Deadline)
15 Jan
1 Apr
9 Aug
Early Admission Deadline
1 Mar
1 May
1 Oct
Regular Admission Deadline
15 Mar
15 May
15 Oct
Programme Start Date
Late Mar/
Early Apr
Early June
Late Oct/
Early Nov
Admission decisions will be made on a rolling basis.
Frequently Asked Questions
Our students come from all around the world and we have become extremely good at coordinating schedules that work for everyone. At the start of every course, we will hammer out the logistics to make sure that we can find a time that works perfectly for everyone involved.
Every video conferencing session will be hosted by a CCIR operations team member. You are welcome to raise the issue through chat at any time. You can also send an email to support@cambridge-research.org, which is monitored at all times during active sessions.
Yes. Every session will be recorded and made available after class. You can access them via an unlisted playlist on YouTube or your Learning Management System.
The only requirements are the Internet (Zoom or compatible browser), front-facing camera, and microphone. Some courses may require specific softwares to be installed. Your mentor and TA will do their best to help you install those softwares.
A number of things differentiate CCIR Academy from other programmes:
IVY-LEAGUE / OXBRIDGE FACULTY AND TEAM
We only partner with current teaching faculty members at top-tier US/UK universities, including Cambridge, Oxford, Harvard, Stanford, MIT, Columbia, Cornell, UPenn, Yale, Dartmouth, and Princeton.
We are also an organisation currently run by Oxbridge students and alumni. Throughout the admission process, every single point of contact an applicant interacts with will be either a current Oxbridge student (PhD or above) or an Oxbridge alumni.
A FOCUS ON PUBLICATION
The goal of CCIR Academy is to push every student to publish their independent research paper to at least an undergraduate or industry level journal or conference. We do not recommend students to publish at predatory pay-for-publish journals or high school level journals. Each student can enjoy the vast research and publication resource that CCIR has to offer, which includes free access to academic database and targeted publication support. As a result, we have great success in having high school students to publish at some undergraduate or even industry level journals and conferences.
SMALL GROUP TEACHING/INTIMATE MENTORSHIP
At the heart of our programmes is the relationship between students and their mentors. For our Cambridge Future Scholar Research Programme, our class is limited to no more than 5 students. The small classes ensure ample interaction and thought provoking discussions always take place at each session.
RESEARCH-ORIENTED LEARNING
Unlike lecture-only programmes, where students learn passively, our programmes emphasize on hand-on research. This kind of project based learning allows students to really dive into the subject and learn in an independent and autonomous manner.
HIGH ACADEMIC STANDARDS
Our commitment to maintaining the highest academic standards is reflected in our admissions, our courses, and in the expectations we have on our students. All our programmes are meant to be genuinely challenging and enriching academic experiences for our students.
Most importantly, by the end of your time at a CCIR programme, you will have completed a substantive independent research project. In certain cases, under the guidance of the mentors and our team, your research project will also be published in academic journals or presented at conferences. All our CCIR programmes award graduation certificates and in-depth evaluation reports. Finally, you will have fostered a close personal relationship with a Oxbridge faculty member from whom you can request a letter of recommendation.
Because of the academic rigor and the small size of our programmes, we are able to deliver an experience for our students that is at once fun and academically enriching. Over the course of the programme, as students work with one another and with the faculty, they will develop relationships that will push them both personally and intellectually.
All our students have the option of requesting letters of recommendation from their mentors. While we cannot guarantee letters of recommendation, we can say that in the past, because our admitted students are all capable and passion at, not a single student who has requested a letter of recommendation has had their request denied.
Attending CCIR may improve your chances in college/graduate admissions in a number of ways. Most importantly, CCIR offers you a great opportunity to produce and possibly even publish a genuinely impressive piece of academic work. In addition, since you will be interacting intimately with your Oxbridge mentor over a long period of time, your mentor will also likely become an excellent referee for you in the admissions process.
Generally speaking, our programmes consist of roughly 1-2 hours of face-to-face interaction hours per week. In addition to the class time, students will be expected to do readings and write essays. On average, including interaction hours, students are expected to devote a total of roughly 4 hours a week for their programme.
All CCIR Academy programmes are conducted online with the support of multiple platforms — video conferencing, learning management systems, etc.
Detailed tuition information, including merit scholarship opportunities, can be found in our programme prospectus.
Most importantly, your tuition covers supervisions, lectures, and additional weekly one-on-one office hours (30 minutes), if requested. Additionally, your tuition covers your access to Cambridge or Oxford’s academic database (via mentor), Data collection guidance (by the mentor), academic journal submission guidance (by the mentor and CCIR Academic Team), and academic support both during the course of the programme and in the follow up (when you need to request letters and evaluations).
To get more information about our programmes, the best way is to download our prospectus through the “Download Prospectus” button on bottom right. If you have more specific questions, please contact our Admissions Team at admissions@cambridge-research.org. If you’re a counselor or a teacher interested in collaborating with our programme, contact Oliver, our Director of Outreach at oliver@cambridge-research.org.
CCIR is looking for students who are not just academically strong but who are genuinely passionate about the subject matter for which they are applying. This means you have to demonstrate academic strength in your GPA and your other test scores (if applicable) and show us that you are someone who possesses a genuine passion for learning.
CCIR’s Future Scholar Programme is designed for sixth form (11th and 12th grade in the US) students. The programme’s curriculum mirrors first-year teaching material at Oxbridge. However, we often receive applications of, and admitted, talented students attending lower levels.
The 1-on-1 Mentorship Programme, on the other hand, is much more flexible. In the past, we have both offered mentorships for younger students who were especially talented and mentorships for undergraduate students.
We are standardized test optional in our admissions. As long as we can see your school transcripts, you’ll be fine.
For the 1-on-1 programmes, our applications are rolling all year round.
For the Future Scholar Programme, applications for these course are all rolling once opened, until the each class is filled at maximum number of five.
All applicants are automatically considered for the merited scholarships. If you face economic hardship and seek financial aid, please inform our Academic Coordinator at apply@cambridge-research.org and we can make arrangements to best accommodate your situation.
We definitely don’t want you to stress over the interview. While there is an evaluative dimension to our interviews, the primary purpose of these interviews is to get a sense of what you have already known about the subject and what your academic passions are. The interviews are all very casual and conversational in style—so just be prepared to come in prepared to chat about your academic interests.
In a word: quite. We are hoping to push you academically and intellectually. However, be assured that you will be closely guided and thoroughly supported throughout this challenging process. And in terms of time commitment, we understand that you are busy so our mentors will ensure that you will not be overloaded with work.
Depending on your project, this may take a number of forms. Survey-based research is a definite possibility, for instance, in the social sciences. In other cases, we instead rely on existing data sets that are either open-source or that are requested from other researchers.
Yes. Many life sciences projects can be completed using existing datasets, computational methods, literature-based analysis, or publicly available research resources. Your mentor can help you develop the scientific computing, data analysis, and research skills required for this type of project.
Please note that CCIR also has a laboratory facility in Boston. Access may be available for projects requiring experimental work, subject to the project’s requirements, mentor supervision, laboratory capacity, and applicable safety regulations.
Our programmes ultimately all adopt a project-based learning methodology. However, the project-based methodology is supplemented by more traditional methods of lecturing and supervision wherever necessary. Worth highlighting is the supervision format of our teaching: this small group teaching style, based on critical peer-to-mentor and peer-to-peer interaction, is a Oxbridge hallmark and one that we have made central to our pedagogical methods.
Our Alumni
