the
Cambridge
Future Scholar
Programme
Explore your passions
through a research
course.
The Future Scholar Programme is an online 2-5 student research-focused programme taught by current teaching faculty members at the University of Cambridge, the University of Oxford, MIT, Harvard, Stanford, and select Ivy League universities.
Each Spring, Summer, and Fall round will be offering 100+ unique research courses in 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
13 weeks of lectures and supervision from Oxbridge or Ivy League faculty mentors and PhD TAs. Curricula mirroring first-year courses at the faculty mentors’ universities.
An Independent Research
Project
Complete an original independent research paper, supervised by an Oxbridge or Ivy League faculty mentor, with the aiming of publication at undergraduate or industry level journals..
A Signed Evaluation
Report
From your Oxbridge or Ivy faculty mentor, issued by the programme, that highlights each student’s performance throughout the programme.
A Letter of
Recommendation
The option to request a tailored letter penned by your Oxbridge or Ivy League faculty mentor.
Download
the Spring 2026
Prospectus for
• Programme structure
• Research course catalogue
• Mentor biographies
• Tuition & Scholarship
Oxbridge Level Writing Centre
Our writing centre, staffed by Oxbridge students and alumni, is constantly on call to provide prompt feedback on your writing.
Independent Ethics Review
Committee
For research involving human subjects, an ERC review is often required to ensure the experiment adheres 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 will not only help you transition from high school to academic writing, we will also actively assist you in getting your work published. Our academic advisors actively maintain our database of publications so that we know how and where to best showcase your work. We will help you avoid predatory academic forums and support you as you publish your work 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 Future Scholar 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 TAs, you will first gain a grounding in your field of research. In addition to 1 hour of lecture a week from your mentor, you will also receive 1 hour of seminar discussion from your TA, and an 30 minute office hour on request.
Research Weeks (8 - 13)
Plan and execute your own research project
Beginning with a research and methodology session, you will then transition into self-directed work. During this research phase of the course, your lecture sessions will become research workshops and your TA sessions will 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
147 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 will talk about the principles of developmental biology and stem cell biology, study organ development (such as the heart), and discuss genome engineering using the CRISPR-Cas9 (a novel genetic modification tool). The objective of the research course is to encourage students to think creatively about how a cell develops an organism, how we can study them experimentally, how we can edit genes, and how we can use animal models to analyse in vivo data.
Brown | BioMed MCB Department
In this research course, each student is tasked to read, digest, and present assigned peer-reviewed research articles in the field of Cell and Developmental Biology, which is the science that investigates how interacting processes generate an organism’s heterogeneous shapes, size, and structural features that arise on the trajectory throughout a life cycle. Topics of interest include asymmetric cell division, cell signalling and metabolism, cellular specification and differentiation, mRNA translation, embryonic development, germ cell and stem cell development, and cancer regulation.
Cambridge | Cambridge Institute for Medical Research
Injury to the brain and spinal cord has devastating consequences as adult neurons in the central nervous system do not repair their nerve fibres. This research course covers the cellular and molecular biology of the nervous system and has a particular focus on the regrowth of nerve fibres after an acute injury – a process called axon regeneration. The independent research project will enable students to gain hands-on experience in the analysis of real experimental data from fluorescence microscopy of neurons and the presentation of scientific results.
Cambridge | Cambridge Institute for Medical Research
As technology advances and scientists pose increasingly complex questions, much of the current research focuses on the intricate relationship between genes, proteins, and their role in biological processes. This research course provides students with hands-on experience using computational tools to predict and analyze the effects of mutations. Students will learn how computational approaches can complement experimental research and drive innovation in drug discovery and disease prevention.
Cambridge | Cambridge Institute for Medical Research
Unlock the secrets hidden in the genome with this hands-on research course focused on modern genomics data analysis. Centered on RNA sequencing, students will explore how gene expression patterns reveal the molecular stories behind cell function, development, and response to environmental changes. Students will work directly with real, publicly available RNA datasets. They will gain practical experience from experimental design to data interpretation, learning how to analyze complex datasets, identify meaningful biological trends, and craft evidence-based scientific narratives.
By the end, students will confidently navigate genomics data, connecting quantitative analysis to real-world biological insights and preparing to contribute to cutting-edge life sciences research.
Princeton | Department of Molecular Biology
In this course, students will receive a comprehensive introduction to the fascinating world of protein biochemistry. We will span several decades of technological advancements including the polymerase chain reaction (PCR), recombinant protein expression technologies, CRISPR/Cas9 gene editing, and advances in optical microscopy approaches. We will combine fundamental concepts in molecular biology and biochemistry with the seminal literature in the field that has led to major scientific breakthroughs and altered the way textbooks are written. Students will explore protein-based machines through independent research projects using basic molecular biology and biochemical techniques (if available) and/or computational AI-based tools.
Oxford | Department of Biochemistry
In this research course, we will explore genetics utilising computational and data scientific techniques. By analysing the vast quantities of data using these cutting-edge techniques, students will learn how to observe and analyze molecular events across the genomes of biological systems.
Cambridge | Department of Genetics
In this research course, students will learn about the role of
genetics in understanding and combatting infectious
diseases, while developing skills relevant in modern computational analyses, known as bioinformatics, which will open
the door for understanding infection mechanisms at the
gene and protein levels.
Cambridge | Department of Pharmacology
In this course, we will learn the basic principles of cancer biology and how to use different bioinformatics tools to analyse health data. We will discuss the hallmarks of cancer to better understand how we can interpret the results we can discover from the data-mining exercises. We will explore large-scale biological data using different bioinformatics tools and platforms. These findings will allow students to uncover genes that can have a potential role as biomarkers or that have therapeutic applications.
Cambridge | School of Clinical Medicine
In today’s era of data-intensive biology, the analysis of biomedical data, from multi-omics and imaging to genomics and phenotypic profiles, is essential for unraveling the complexities of human health and disease. By the end of the research course, students will be equipped with a robust understanding of both biological data analysis and the AI-driven tools that are reshaping today’s biomedical research.
Cambridge | Department of Pharmacology
In this course, we will learn the basic principles of genomics and molecular profiling approaches used to analyse an individual’s genetic information. We will also engage in hands-on research by utilising bioinformatics tools to identify biomarkers—specific indicators associated with particular diseases or treatment responses. As precision medicine involves integrating data from various omics sources, such as genomics, transcriptomics, proteomics, and metabolomics, we will use bioinformatics tools to explore and integrate multi-dimensional data, offering a more comprehensive view of biological processes. The potential role of artificial intelligence, machine learning and other innovative approaches in shaping the future of precision medicine will also be discussed.
UC Berkeley | Landry Lab, Department of Chemical and Biomolecular Engineering
This research course will cover emerging topics in applied biotechnology – from CRISPR to cloning. We will learn the fundamental principles of DNA, RNA, and protein biochemistry and think about how analogous techniques to study and analyse these systems have emerged. Next, we will discuss the development of CRISPR-based genome editing applications. The scope of the research course will allow students to probe the cutting-edge interface of biology with engineering.
UC Berkeley | Landry Lab, Department of Chemical and Biomolecular Engineering
This research course will focus on technologies to monitor and manipulate the brain and the nervous system, including implantable medical devices, fundamental neurobiology, and brain-machine interface applications. This comprehensive research course will tackle technologies leveraged to treat neuropsychiatric and neurodegenerative disorders such as Parkinson’s disease, Alzheimer’s disease, schizophrenia, depression, anxiety, and social autism spectrum disorders.
Oxford | Department of Biochemistry
DNA damage comes in many forms. Left unrepaired, these lesions can lead to mutations, cell death, or cancer. To guard against this, our cells rely on the DNA damage response (DDR)—a sophisticated network that detects, signals, and repairs DNA damage with remarkable precision. This cellular defence system is not only vital for maintaining genomic stability but also central to our understanding of cancer development and treatment.
This research course will centre around one of the most critical questions in modern biology and medicine: how do our cells protect their genetic code from daily assaults—and what happens when they fail? Students will delve into the sophisticated mechanisms of the DNA damage response, uncovering how cells detect, signal, and repair various forms of DNA damage.
Harvard | Joslin Diabetes Center
Throughout the research course, students will explore cutting-edge strategies and technologies used in drug discovery with a focus on metabolism-targeting therapeutics. The rapidly advancing field of drug development offers various approaches, including novel drug design, high-throughput screening methods, and precision medicine techniques. By exposing students to these state-of-the-art methodologies, the course aims to equip them with the knowledge and skills necessary to engage in contemporary research efforts and contribute to the development of next-generation drugs aimed at combating metabolic diseases.
Harvard | Massachusetts General Hospital
Regenerative medicine, using biologically compatible materials (biomaterials) and stem cells, aims to restore the functions of damaged organs or tissues. We will examine the basics of stem cell biology, explore different types of biomaterials, discuss current tissue engineering strategies and commercially available tissue engineering products. Ultimately, students will each conduct a research project in which participants can develop their own hypothetical
tissue engineering strategies to restore a type of tissue of their own choosing.
Cambridge | Department of Veterinary Medicine
This course offers an introduction to bacterial genomics within the context of the pressing global concern—antimicrobial resistance (AMR). Students delve into resistance genes, horizontal gene transfer, and cutting-edge DNA sequencing techniques, gaining practical skills in bioinformatics for AMR surveillance. The course goes beyond theoretical understanding, exploring strategies to combat AMR, including responsible antibiotic use, alternative therapies, and global initiatives. Emphasis is placed on hands-on exercises, discussions, and collaborative projects that empower students to analyse real-world genomic data and propose solutions to address AMR challenges.
Princeton | Molecular Biology Department
Analytical chemistry plays a crucial role in modern science, particularly in areas such as disease biomarker detection, biosensor development, and gene-editing technologies. In this research course, students will explore the fundamental concepts of disease biomarkers and their applications in disease diagnosis, delving into how chemical analysis techniques achieve high sensitivity and specificity in detection. The research course also focuses on the principles and design of biosensors, including the integration of nanomaterials and chemical modification techniques to enhance sensing performance.
UC Berkeley | University & Jepson Herbaria
This is a hands-on, interdisciplinary research course that introduces students to the science of biological diversity and the many ways it is studied and understood. Biodiversity refers not only to the number of species in a given area but also to how those species interact, function, and vary across space and time. Students will learn how scientists use different metrics to quantify biodiversity, including species richness, evenness, abundance, beta diversity, and functional diversity, and explore what each metric reveals about ecosystems. These concepts will be illustrated through examples drawn from a range of organisms, including plants, animals, and fungi, highlighting the complexity and importance of life on Earth.
Cambridge | Department of Veterinary Medicine
Zoonotic diseases, where pathogens jump from animals to humans, pose a major global health threat and account for nearly 75 percent of emerging infectious diseases. This research course explores the molecular and evolutionary processes behind host-switching by using whole-genome sequencing and bioinformatics tools to uncover how viruses and bacteria adapt to new hosts. Students will study important cases such as SARS-CoV-2, avian influenza, and bovine tuberculosis to understand how genetic changes allow pathogens to cross species boundaries, preparing them to address critical global health challenges.
Oxford | Centre of Medicine Discovery
Rare diseases affect people across diverse biological systems but often remain poorly understood, leading to delayed diagnoses, limited treatments, and significant emotional and social challenges. This research course will explore the science behind rare diseases using Congenital Dyserythropoietic Anaemia 1 (CDA-1) as a case study while also examining the real-world impact on patients, families, and healthcare systems. Working closely with a CDA-1 patient charity and researchers, students will develop skills in research, scientific writing, and communication as they engage with the ethical and societal dimensions of rare disease medicine.
Cambridge | Department of Engineering
Our brain controls how we perceive our surroundings and
how we interact with them, how we feel, and who we are. In
this research course, we will explore how the brain and
nervous system function with a particular attention to its
core building block – the neuron. We will also explore how
technology can be utilised to better understand and treat
the brain.
Columbia | Department of Psychology
This research course offers students a stimulating opportunity to study the brain and its relationship to behaviour and mental processes. It is designed to be accessible, engaging, and intellectually enriching for students with no prior background or formal training in neuroscience. Students will begin by exploring the fundamental building blocks of the nervous system, learning about brain anatomy and organisation, how neurons work and communicate, and the methods scientists use to study the brain, including brain imaging and clinical case studies. From there, students will examine how the brain processes sensory information, with a focus on vision and perception, and how it supports higher-order functions like language and communication, attention and awareness, and decision-making and problem solving.
Harvard | Harvard Medical School
What is the nervous system, and how does it shape our thoughts, behaviors, and mental processes? This research course offers a comprehensive introduction to the field of neuroscience, exploring the structure and function of the nervous system from the molecular to the cognitive level. It invites students to consider the biological principles that underlie neural activity, behavior, and mental processes. Key topics will include synaptic transmission, neuroplasticity, sensory and motor systems, and the biological bases of learning and memory.
Stanford | Department of Psychiatry and Behavioral Sciences
This research course invites students to investigate the powerful role of AI in neuroscience research. Students will explore how tools such as computer vision and computational modeling are revolutionizing the study of behavior by allowing researchers to track social interactions with unprecedented precision and link them to underlying patterns of brain activity. These methods are reshaping our understanding of how experiences influence social behavior and how responses shift depending on context. For example students will examine how algorithms can detect when two animals are investigating one another or when one displays aggressive behavior–and how these observations are linked to specific brain circuits. Such case studies help answer foundational questions like: How do experiences rewire the brain? Why do some animals become more social while others become more withdrawn?
Cambridge | Cavendish Laboratory
Recent breakthroughs in deep learning and large-scale medical imaging datasets are transforming how clinicians interpret CT and MRI scans. The research course covers fundamental principles of image processing, anatomical context, and advanced AI methods that boost model reliability and transparency in medical imaging. Through hands-on Python programming, students will build AI pipelines from data preprocessing to model training and explainability analysis using real clinical imaging datasets.
Oxford | Department of Experimental Psychology
This research course will examine the building blocks of human intelligence through the lenses of cognitive psychology. We will explore the fundamental cognitive processes such as attention, memory, and learning. We will then examine how these core abilities give rise to more complex processes such as decision making, problem solving and abstract thinking, and ultimately to what we consider intelligent behaviour. The overall aim of the course is to provide students with a thorough understanding of the key topics in cognitive psychology, to provide a space to integrate theoretical and experimental knowledge, and equip students with a thorough understanding of the tools and approaches used to study cognition.
Oxford | Department of Experimental Psychology
What is the relationship between Arts and the human psyche? Why does art exist? From a psychological point of view, why do we as humans need art? This research course offers an interdisciplinary approach to understanding arts. It brings together insights from psychology and neuroscience, and practical applications of art in psychotherapy and mental health work. The key focus of the research course will be on the art as an expression of our psychological worlds – that is, the relationship between art and the human psyche.
Harvard (Harvard Medical School) | Beth Israel Deaconess Medical Center, Boston
The blood-brain barrier is a major field in neuroscience, because it protects the brain from harmful substances in the blood while allowing essential nutrients to pass through. In this research course, we will grasp the essential concepts in cellular and molecular medicine, neuroscience, and genetics, specifically focusing 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 offers a comprehensive introduction to the foundational principles of stem cell biology and the emerging and transformative field of regenerative medicine. It is designed for students seeking to understand the dynamic role of stem cells in both biological research and clinical applications. This foundation will equip students with the knowledge needed to pursue further studies or a career in stem cell science and regenerative medicine, fostering their contribution to one of the most promising and rapidly evolving areas of modern biology.
Oxford | Department of Physiology Anatomy and Genetics
Tissue loss from injury, disease, or aging often leads to permanent impairments because many organs, especially the brain, have limited ability to regenerate. Stem cells, with their unique ability to self-renew and become specialized cells, offer exciting possibilities for repairing or replacing damaged tissue. Through critical analysis of primary research and case studies, students will examine cellular mechanisms, reprogramming technologies like induced pluripotent stem cells, and approaches involving cell transplantation and tissue engineering. They will also design independent research projects to evaluate or propose regenerative strategies.
Dartmouth | Computational and Cognitive Neuroscience Lab, Department of Psychological and Brain Sciences
In this research course, we will examine decision making from both behavioural and neurobiological points of view. Specifically, we will learn about different methods used in psychology and neuroscience to study decision making at various levels, from mental and cognitive processes to underpinning neural activity and mechanisms. Ultimately, this research course will alter students’ perspectives on decision-making by imparting knowledge of brain function.
Dartmouth | Computational and Cognitive Neuroscience Lab, Department of Psychological and Brain Sciences
Neuroeconomics is a new emerging field in which a combination of methods from neuroscience, psychology, and economics is used to better understand how we make decisions. Neuroeconomics uses various cutting edge techniques to study how the brain integrates information from various sources. In this research course, we learn about economic and psychological theories that are used to investigate and understand choice behaviour, as well as mental and neural processes that underlie decision-making.
Oxford | Department of Experimental Psychology
This research course delves into the fascinating realm of how the human brain supports learning and decision-making processes, drawing insights from computational neuroscience. Throughout the course, we will explore fundamental concepts such as reinforcement learning and Bayesian decision theory, unravelling the intricate mechanisms that underlie our cognitive abilities. By synthesising insights from neuroscience, psychology, and computer science, students will develop a holistic understanding of human learning and decision-making processes. In summary, this course offers a multidisciplinary perspective that will deepen students’ understanding of the complex interplay between the brain, behaviour, and computational principles.
Cambridge | Department of Psychology
Motivation and emotion are critical functions of the brain,
allowing individuals to enhance their likelihood of survival
and passing on their genes. In this research course, we will
aim to provide a foundation of research, theory and
practical skills acting as a primer for the student interested
in the psychological and neural basis of emotion, motivated behaviours and the mechanisms of abnormal emotion
and motivation.
Cambridge | Department of Psychology
In this research course, we will explore foundational research, theory and practical skills related to molecular and systems pharmacology of central nervous system disorders. The course will provide the students with a solid background in cellular and molecular neuroscience, neuropharmacology and behavioural neuroscience that will then be used to discuss the neuropsychopharmacology of neuropsychiatric disorders. The aim of this research course is to provide an understanding of the chemical pathology of the major central nervous system diseases/disorders, and how these conditions are treated with drugs.
Harvard (Harvard Medical School) | Dettmer Lab, Department of Neurology
In this research course, students will deepen their under- standing of brain anatomy, brain biology and the degeneration that occurs in Parkinson’s disease and causes the hallmarks of PD. Potential intervention strategies will be evaluated. The importance of biomarkers for diagnosis and drug development will be discussed, and potential biomarker strategies will be highlighted. The goal is to outline novel strategies towards (early) diagnosis and treatment of PD, and this may include the combination of different approaches.
Oxford | Department of Engineering Science
This research course provides a comprehensive exploration of the essential engineering principles of thermofluids, aerodynamics, and experimental design, equipping students with the theoretical knowledge and practical skills needed to address challenges in aerospace, energy, and sustainable technologies. Students will be prepared to apply these skills to innovate and create solutions for achieving sustainability and net-zero objectives in the industries of aerospace, sustainable energy, industrial systems, and beyond.
University College London
DNA molecules have particular chemical and physical properties that can be applied to solve tasks that go beyond the scope of their function in nature. In this research course, we will explore first DNA’s functional characteristics and how can they be used to produce complex architectures at the nanoscale that can then perform customised tasks for a wide range of applications – from biomedicine to the manufacturing industry, including data storage and complex chemical production.
UCL | Department of Computer Science
Biorobotics is a cutting-edge interdisciplinary science at the intersection of biology, biomedical engineering, computer science and robotics. It studies ways to improve the intelligence, locomotion, and other performances of robotic systems inspired by nature. In this research course, students will be introduced to novel bio-inspired ideas that have revolutionised modern day robotics, particularly in the field of soft-robotics. The course delves into the principles and methods behind the design of physically compliant robots. Students will learn the programming language MATLAB and develop their independent research projects on bio-inspired robotics.
Cambridge | Bio-Inspired Robotics Lab
This research course introduces students to the intersection of robotics and artificial intelligence, with a focus on the machine learning techniques that power advancements in modern robotics. Covering a broad spectrum of intelligence levels, the research course begins with foundational concepts, such as understanding touch and interaction with the physical environment, and progresses to advanced methodologies, including reinforcement learning, learning from human demonstrations, and multi-agent collaboration.
UCL | Department of Medical Physics and Biomedical Engineering
Soft robotics is a rising branch of robotics that aims to develop delicate, flexible and safe robotic devices which interact with humans using soft actuators that mimic biological behaviour, which state of the art rigid robots cannot accomplish otherwise. In practice, they can perform tasks that would be impossible or dangerous for humans to do. This research course will introduce students to this nascent branch of robotics and have a deeper insight into soft robots’ concept, development, and control. With this, the students will develop a full awareness of the topics, which will allow them to work on their independent research projects.
UC Berkeley | College of Engineering
This research course provides preparation for the conceptual design and prototyping of mechanical systems that use microprocessors to control machine activities, acquire and analyse data, and interact with operators. Students will perform laboratory exercises that lead through studies of different levels of software. Software coverage includes C and Matlab. Students will have the opportunity to work with an Infineon PSOC6 microcontroller.
Oxford | Department of Engineering
In this research course, we will explore the fundamental principles of mechanics in this comprehensive course that covers the essential and advanced concepts of statics and dynamics. Throughout the research course, hands-on exercises, problem-solving sessions, and interactive simulations will allow students to apply theoretical concepts to practical situations. By the end of this course, students will possess a solid understanding of basic mechanics, enabling them to analyse static equilibrium, assess structural members, and predict the behaviour of particles and rigid bodies in dynamic situations.
Cambridge | Department of Medicine / Department of Engineering
Nanotechnology is a multidisciplinary field that draws from physics, chemistry, biology, and engineering. It is a rapidly evolving field that offers novel solutions for many industrial challenges. In this research course, students will learn about various aspects of nanotechnology and nanomaterials, and how they are applied to create devices such as solar cells, superconductors, and medical sensors.
Cambridge | Department of Medicine / Department of Engineering
This research course covers the entire process of sensor data science: data collection, pre-processing, feature extraction, and machine learning modelling. Mobile and wearable sensors will be mainly used, and the types of sensor data covered include motion (e.g. vibration/acceleration, GPS), physiological signals (e.g. heart rate, skin temperature), and interaction data (e.g. app usage). Students will learn the basic digital signal processing and feature extraction techniques. Basic machine learning techniques will be reviewed, and students will master these techniques with a final mini-project to solve real-world sensor data science problems.
Cambridge | Department of Engineering
Wearable bioelectronics are revolutionizing how we monitor the human body, powering everything from smartwatches to advanced medical sensors. Students will explore the science behind these devices, starting with the fundamentals, and design an independent project focused on a wearable bioelectronics application that interests them, such as cardiac monitoring or sleep-stage classification. Students will understand wearable health technologies deeply and confidently apply engineering and data science to solve real-world problems in biomedical engineering, neuroscience, and digital health.
Cambridge | Department of Engineering
This research course offers a unique opportunity to explore how cutting-edge materials and technologies can redefine the future of the built environment and contribute to the global transition towards a net-zero carbon society. It invites students to explore and engage with the latest advances in materials and technologies that are transforming the construction industry, equipping them with the skills and knowledge needed to engineer sustainable solutions for the next generation of infrastructure. It will delve into next-generation cementitious materials, including low-carbon and alternative cements, self-healing composites, and circular material systems designed to maximise resource efficiency by repurposing construction and demolition waste.
Cambridge | Faculty of Philosophy
This research course will delve into the intricate relationship between mathematics and philosophy. Students will explore topics such as mathematical logic, set theory, and computability theory. The aim of this course is to inspire students to engage in independent research projects focusing on fundamental questions in mathematics, logic, and philosophy. Through this exploration, students will gain a fresh perspective on mathematics and its connection to broader philosophical inquiries.
Cambridge | Department of Computer Science and Technology
This research course is designed for students with a keen interest in computer science, mathematics, or related disciplines who want to develop a strong mathematical foundation. Mathematics lies at the core of computer science and programming, providing the tools to understand and analyze the algorithms and structures that underpin modern computation. Through this research course, students will explore essential mathematical concepts such as discrete mathematics, set theory, logic, probability, and algebra, all of which are crucial for understanding the theoretical and practical aspects of computer science.
Cambridge | Department of Computer Science and Technology
For millennia, humanity has pondered the nature of reasoning and whether it can be governed by clear rules. The quest for these “simple enough” rules, rooted in basic principles yet powerful enough to encompass various processes, spurred the development of mathematical logic and theoretical models of computation. This research course explores this historical journey, from Euclid’s axioms to the works of Frege, Peano, Russell, Gödel, and Turing, delving into formal systems, Gödel’s incompleteness theorems, and computational models like recursive functions and Turing machines. Bridging theory and practice, students explore automated reasoning and interactive theorem proving, gaining insight into the potential and limitations of formal systems, thus equipping them with tools for their development and application.
Cambridge | Department of Computer Science and Technology
Natural language processing (NLP) is a field of artificial
intelligence that has seen significant development in recent years with current applications include virtual assistants, language translation tools, and sentiment analysis for social media. In this research course, students will learn about the fundamental techniques for processing language for several subtasks, such as morphological processing, parsing, word sense disambiguation, etc. They will also have the opportunity to explore the various applications of these techniques in real-world scenarios.
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 offers a rigorous introduction to core ML principles and methods with a focus on scientifically sound model development and evaluation. Students gain hands-on experience implementing supervised learning algorithms on real-world datasets while exploring unsupervised and reinforcement learning concepts. This research course prepares students to critically assess ML algorithms, understand their role within AI, and apply rigorous methods to real-world challenges like sentiment analysis and beyond.
Cambridge | Department of Computer Science and Technology
In this research course, we will first systematically introduce the fundamental tasks and typical applications of NLP, such as sentiment analysis, machine translation, and text summarisation. We will then introduce pre-training technologies, such as masked language modeling and autoregressive language modelling, and representative pre-trained language models (PLMs), including BERT and GPT, along with their architectures. Building on these, we will discuss how these PLMs scale up to LLMs. On this basis, students will conduct a hands-on research project to apply LLMs to real-world tasks and critically examine their strengths and limitations.
Cambridge | Language Technology Lab
In this research course, we will explore key concepts in Deep Learning and Natural Language Processing. Hands-on components will let the students build and train deep learning models, fine-tune advanced language models like GPTs. This research course offers a transformative experience, gearing the students up for future academic and professional pursuits in AI.
Cambridge | School of Clinical Medicine
The focus of this research course is learning end-to-end
models for these tasks, particularly image classification and
segmentation, using machine learning architectures. During
this course, students will gain a detailed understanding of
cutting-edge research in the fields of artificial intelligence,
computer vision, and artificial neural networks. Additionally,
the final assignment will allow them to apply their hands-on
knowledge to real-world vision problems.
Oxford | Department of Engineering Science
This research course provides a comprehensive introduction to deep learning techniques tailored for computer vision and medical image analysis. Through a combination of theoretical discussions and hands-on projects, students will explore techniques for image classification, segmentation, object detection, and anomaly detection. By the end, students will have able to design, train, and evaluate state-of-the-art models for a variety of computer vision tasks.
Oxford | Department of Engineering Science
This research course delves into the cutting-edge advancements in artificial intelligence, with a particular focus on the latest trends, i.e, foundation models and multimodal large language models (LLMs), such as GPT, BERT, and DALL-E. The research course examines the architectures and training paradigms underpinning these models, including self-supervised learning, attention mechanisms, and scaling laws.
Cambridge | School of Clinical Medicine
This research course introduces students to large-scale language models like GPT, exploring how machines comprehend and generate human-like text. It blends theory with practical exercises in natural language processing, aiming to demystify AI and inspire further study and careers in technology. Beginning with intensive introductions to machine learning and neural networks, the course progresses to independent research projects supervised by faculty. Students delve into advanced NLP techniques and are prompted to consider the ethical implications and boundaries of AI.
Imperial College London | Department of Computing
This research course delves into the realm of Natural Language Processing (NLP) and Large Language Models (LLMs), such as ChatGPT, which have revolutionised various domains but are prone to errors with significant implications. It aims to equip students with NLP tools to analyse, understand, and mitigate LLM errors. Beginning with NLP basics, the course explores LLM principles, architecture, and training methods, fostering hands-on experience with state-of-the-art tools for error analysis. Students engage in ethical discussions on AI deployment and decision-making, emphasising accountability and fairness. Through independent research projects, students investigate LLM errors, developing critical thinking and problem-solving skills essential for responsible AI development.
University of California | School of Information
The proliferation of smart spaces, ranging from intelligent homes and offices to advanced urban environments, has resulted in an explosion of video data generated by connected devices such as surveillance cameras, drones, and IoT-enabled sensors. Harnessing this data effectively requires a unique intersection of expertise in data science, distributed systems, and video analytics. This course aims to equip students with the knowledge and skills to design, implement, and optimize systems for processing and analyzing video data in smart spaces.
University of California | School of Information
This research course offers an in-depth exploration of data science, blending foundational principles with hands-on applications to equip students with the skills needed for real-world challenges. We will also delve into large language models (LLMs), such as GPT, and their transformative role in modern data science. Through practical projects, students will have a comprehensive understanding of the data science pipeline, from data preparation to advanced machine learning and AI integration.
Cambridge | Centre for Advanced Research and Education
Artificial Intelligence and Machine Learning are transforming industries and driving innovation across diverse fields, from healthcare to finance to environmental sustainability. This research course explores real-world applications of AI and ML, showcasing how these tools are used to address critical challenges, including vaccine development in the case of Moderna, text mining for stock market prediction, to computer vision for autonomous robots, and many more.
UCLA | Department of Communication
This research course explores the application of data science to real-world problems across sociology, psychology, public health, education, journalism, and political science. By the end of the research course, students will be able to critically analyze social data, apply machine learning techniques to real-world problems, and effectively communicate findings to diverse audiences. They will develop proficiency in using computational tools for data-driven decision-making and gain experience in addressing ethical considerations in data science applications.
Cambridge | Department of Applied Mathematics & Theoretical Physics
Climate change is among the most significant existential threats facing humanity, driving increased frequency and intensity of environmental hazards, ecosystem degradation, and widespread societal challenges.This research course aims to equip participants with the
knowledge and skills to analyze climate change and environmental risks using machine learning, bridging
scientific understanding and data-driven solutions.Students will have the opportunity to engage with algorithms and datasets, applying theoretical knowledge to pressing climate and environmental issues.
Cambridge | Department of Computer Science and Technology
This research course is an in-depth exploration of the realm of social networks, arguably the most important platform for collaboration and communication among the global population. We will explore the widespread adoption of social media platforms such as Facebook, Twitter, Instagram etc., which enable users to share diverse content like opinions, experiences, perspectives, and various media formats. Additionally, students will be taught cutting-edge methodologies for analysing and visualising data pertaining to social network structures and dynamics.
Oxford | Department of Engineering Science
In this research course, students will gain an understanding
of how AI-based technologies are revolutionising healthcare.
Students will be introduced to biomedical sensors and
wearable systems and gain knowledge on the underlying
physiological phenomena. They will also learn to programme
in Python/MATLAB and implement their own AI pipeline on
healthcare data, from scratch.
Cambridge | Innovation Centre for Digital Molecular Technologies
In this multidisciplinary research course, students will explore the rise of machine learning (or artificial intelligence) with specific reference to drug discovery and chemical development, as well as emerging techniques for effective chemical/pharmaceutical synthesis. Combining topics from chemistry, biology, chemical engineering, and computer science, the research course equips students with the interdisciplinary knowledge needed to tackle cutting-edge problems in these fields.
Oxford | Saïd Business School / Deep Learning Partnership
Scientific discovery has traditionally relied on human intuition, hypothesis formation, and experimental validation—a process that can take decades to yield breakthrough insights. This research course will explore how artificial intelligence is fundamentally transforming the discovery process, empowering students to work at the forefront of computational science and machine learning.
Students will investigate how modern AI systems can autonomously generate novel scientific hypotheses, design experiments, and identify patterns not apparent to human researchers. This research course focuses on three central themes: automated hypothesis generation using large language models and knowledge graphs, AI-driven experimental design optimization, and the development of discovery algorithms capable of navigating complex parameter spaces more efficiently than traditional methods.
Oxford | Saïd Business School / Deep Learning Partnership
In the course, students will master the latest machine learning techniques specifically designed for scientific applications, including deep learning architectures for time-series analysis, computer vision methods for microscopy, astrophysics and medical imaging, and LLMs for literature mining, genome sequencing and drug discovery, both supervised and unsupervised learning approaches will be taught to help students extract patterns from labeled datasets and discover hidden structures in unlabeled data.
Princeton | Department of Chemistry
This research course invites students to the exciting intersection of artificial intelligence (AI) and optical imaging in the context of biological research. Students will explore how modern imaging technologies—such as brightfield, fluorescence, and confocal microscopy—are used to capture complex biological phenomena. Alongside this foundation in imaging, students will learn how machine learning (ML) and deep learning techniques can be applied to analyze, interpret, and classify biological data.
Harvard | The Institute for Quantitative Social Science (IQSS)
This research course equips students with advanced statistical, machine learning, and AI methods to address complex social science issues such as political polarisation, gerrymandering, and criminal justice. It aims to demystify these methods and provide practical guidance on their evaluation and application. Through hands-on experience with real-world datasets, students learn to use tools like GitHub and cloud computing for analysis. The course covers a range of methods including Ordinary Least Squares, Bayesian statistics, Large Language Models, and survey methods, preparing students to communicate results effectively to policymakers and the public.
Super Computer Center | MIT / UC San Diego / US Navy
Quantum computing is poised to revolutionize technology and science by tackling problems classical computers cannot solve. This research course offers a comprehensive and intuitive introduction to quantum computing—from the mind-bending quantum phenomena of superposition and entanglement to practical programming on real quantum hardware using IBM Q and Qiskit. Designed for students across disciplines, this course requires no advanced physics or mathematics. Instead, it focuses on visual and hands-on learning, using computer graphics and real experimental data to bring quantum behavior to life.
Cambridge | Department of Applied Mathematics and Theoretical Physics
This research course will provide an introduction to quantum processes. We will begin by expounding the principles of quantum mechanics in our setting (and Dirac notation) and then immediately make connections to information (quantum states viewed as information carriers, quantum teleportation) and computation (notion of qubits and quantum gates). At the same time, we will discuss quantum cryptography (quantum key distribution), and quantum computing, culminating in an exposition of principal quantum algorithms, such as the Deutsch-Jozsa algorithm. While no previous knowledge of quantum physics is required for this course, a relatively strong background in mathematics or physics would be beneficial.
Princeton | Department of Chemistry
This research course focuses on classic light-matter interactions, delving into the realm of physical chemistry, with a special emphasis on photoluminescence. Throughout the course, students will grasp the fundamental principles of light-matter interactions, including basic quantum mechanics to extend their understanding from classical to quantum physics. Through hands-on experimentation, they will cultivate a deeper understanding of the dynamic processes that govern the interplay of light and matter.
Cambridge | Centre for Quantum Information and Foundations
Quantum physics is confirmed with overwhelming experimental evidence at the microscopic scales (e.g., at the atomic scale), producing many technological applications. This research course will address the foundational issues of quantum physics as it relates to quantum measurement and general relativity. Students with a relatively strong background in mathematics or physics would excel in this research course.
Cambridge | Centre for Quantum Information and Foundations
General relativity (GR) is one of our two fundamental theories of physics (together with quantum theory). According to general relativity, space and time are part of a single entity called spacetime, whose geometry depends on the distribution of energy and mass according to Einstein’s equations. In this research course we will discuss the theory of general relativity and some fascinating applications and important open problems, including curved spacetime, gravitational lensing, black holes, gravitational waves, and more.
MIT | Kavli Institute for Astrophysics and Space Research
Astronomy is entering an unprecedented era of big data, as
new facilities are observing more phenomena than humans
can possibly visually examine. Dealing with millions of
astronomical objects and producing terabytes of data every
day requires machine learning and statistical methods to
classify, model, and characterise the data influx. In this
research course, we will learn cutting-edge machine-learning
methods and apply them to real astronomical datasets to
discover, model, and further our understanding of the
universe
MIT | Kavli Institute for Astrophysics and Space Research
The measurement of cosmic distances provides the essential framework for understanding the origin, evolution, and fate of our universe. This research course explores the intricate “cosmic distance ladder” – the interconnected methods astronomers use to measure distances from our solar neighborhood to the edge of the observable universe. Through hands-on projects with real astronomical datasets, students will answer one of the most fundamental questions, what is the origin, structure, and future of the universe?
Oxford | Department of Physics
White dwarfs, neutron stars and black holes are compact
objects forming at the final stages of the evolution of
massive stars. In this research course, we will learn the
nature of compact objects and see their place in the history
of the universe. During the research course, we will touch
on many topics from high energy astrophysics and talk
about the recent progress in the detection of gravitational
waves. Finally, we will discuss open issues standing in front
of the scientific community and try to figure out how further
steps in the investigation of black holes, neutron stars, and
white dwarfs will help in probes of fundamental physics
under extreme conditions.
Oxford | Department of Physics
This research course deals with the structure and evolution of isolated stars and starts in binary systems.Through a blend of theoretical concepts, observational data, and computational models, student will gain an understanding of the physical phenomena governing stars’ evolution. Throughout the research course, students will engage in hands-on activities, computer simulations, and observational projects to reinforce theoretical concepts and gain practical skills in data analysis.
Oxford | Beecroft Institute for Particle Astrophysics and Cosmology
Our standard model of cosmology posits that around 85% of the matter in the universe is “dark matter”: an elusive, invisible, hypothetical substance that interacts noticeably with ordinary matter only through gravity. A key challenge in astrophysics is mapping out dark matter using subtle observations that give us clues to its gravitational influence, such as the arrangement of billions of galaxies photographed by telescopes and the bending of light by dark matter’s gravity. We will gain hands-on experience with advanced statistical techniques and machine learning methods, utilizing the same tools used by leading academic researchers in the field that allows us to unravel its secrets.
University of Toronto | Canadian Institute for Theoretical Astrophysics
Black holes are among the most enigmatic and extreme objects in our universe. Though they consist solely of gravity, the no-hair theorem tells us that their only defining properties are mass, spin, and charge. Despite this simplicity, they give rise to some of the most complex and energetic phenomena in astrophysics. In this research course, we will explore what black holes are and how we can “see” them—not directly, but through the radiation emitted by matter and plasma in their immediate vicinity.
Cambridge | Institute of Astronomy
In this research course students will learn what makes a planet habitable, the techniques employed by exoplanet astronomers, how astronomers will identify life on other planets (including what molecules can be signatures of biological activity), and computational skills relevant for exploring different exoplanet properties. Students will gain experience in Python and use online exoplanet databases to analyse current planetary demographics. This will support independent research projects, ranging from identifying promising habitable candidates to studying statistical trends among terrestrial (rocky), sub-Neptune, Neptune, and Jupiter-sized exoplanets.
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.
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.
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 | 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.
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.
KU Leuven (US News World Top 50) | Department of Economics
This research course explores Game Theory, an interdisciplinary field that delves into strategic decision-making across different domains. Game Theory uncovers hidden strategies and dynamics behind decision-making in diverse situations, influencing individuals, organisations, nations, and animals. By the end of the course, interactive discussions, case studies, and real-world examples will have enriched the students’ understanding of game theory concepts, fostering a solid foundation in strategic thinking across diverse contexts.
UPenn | Yale, Computational Social Science Lab | Human Nature Lab
This course in network science explores how connections and relationships shape the world around us, from social interactions to technological systems. Networks exist everywhere—whether in friendships on social media, road systems, or biological processes—and provide a powerful way to model complex systems. Through graphs, simulations, and computational models, we will study the fundamental structures of networks and their impact on human behavior.
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.
Columbia | Department of Sociology
Bodies are central to the human experience. We move, function in society, and make sense of our existence and relatedness through our bodies. However, within our societies, not all bodies are treated equally. Based on social rules and norms, some bodies are deemed deviant, incomplete, marginalised, or less than, compared to others. This research course invites students to critically explore the relationship between intersectionality and the body. Through engaging with thought-provoking literature, this course will open up discussions about how bodies are disciplined, moulded, surveyed, and the hierarchies formed around bodies.
Cambridge | 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, Centre for Socio-Legal Studies | University of Toronto, Department of Sociology
This research course delves into violence, exploring its meaning, origins, and manifestations. It examines debates on defining and documenting violence, focusing on distinguishing interpersonal from state-sanctioned violence. The course analyses societal, cultural, and individual factors influencing violent behaviour, including legal frameworks and power dynamics. It scrutinises colonial legacies’ impact on violence and how racial and gender dynamics intersect with it. Overall, the course aims to provide a comprehensive understanding of violence as a complex social phenomenon shaped by historical influences, power dynamics, and cultural contexts.
Oxford, Centre for Socio-Legal Studies | University of Toronto, Department of Sociology
Crime stories do more than report facts. They shape how society sees danger, justice, and social order. From news outlets and true-crime podcasts to streaming documentaries and social media, most people’s understanding of the criminal justice system comes from media narratives that decide who is dangerous and what justice means. This research course explores crime not as an objective fact but as a cultural and political story shaped by the media. Students will analyze how new media formats and digital platforms shape public views of crime and influence policy and fear. Through critical analysis and real-world examples, students will build skills to spot manipulation, question narratives, and understand how crime stories support social control or challenge authority.
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.
Cambridge | 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. The relationship between technology and society takes shape through where and by whom that particular technology is developed, who has control over it, who is able to access it and under which circumstances, who it serves, and what social problems it engenders while attempting to solve others.
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.
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.
Cambridge | Cambridge Judge Business School
Investments, securities, markets, bonds, trading…This is a dynamic and engaging research course designed to explore the fascinating world of finance. It will provide students with a solid foundation in financial markets, trading, and the principles that drive stock prices, making it perfect for those interested in pursuing careers in business, economics, or investing, simply wanting to understand how financial markets operate.
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.
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
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.
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.
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.
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.
Cambridge | Department of History and Philosophy of Science
This research course explores how science and technology have evolved since the eighteenth century, transforming human understanding and shaping societies worldwide. Students will analyze the social, economic, and political conditions that have influenced science and technology, developing skills to think critically about innovation on both local and global scales. Through diverse case studies and interdisciplinary research, they will uncover the complex connections between imperialism, industrialization, and the professionalization of scientific disciplines.
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 | History of Art
This research course will explore some of the most significant writings about art from antiquity to the present, guiding students through how art has been understood, debated, and valued across time. Starting with the Greek definition of art as mimesis (imitation), the course traces evolving ideas about the nature of art, its relationship to truth, beauty, morality, and society.
We will examine enduring questions: What is art? Can art tell the truth—or does it deceive? Why do we celebrate artistic realism, and what kind of truth (if any) does it reveal? Is beauty objective or subjective? Can art access invisible, higher truths? What makes art meaningful, and how has that changed across time and culture?
U Chicago | Department of History
The aim of this course is to introduce a history of contemporary art from China since the 1970s. The course begins with a brief overview of modern art activities in China during the early 20th century along with art production under Mao. The course will then focus on contemporary avant-garde movements during the 1970s and 1980s, the response to urbanisation in art at the onset of the new millennium, the influence of globalisation since 2000, and a new generation of young artists from China as well as Chinese diasporic artists working transnationally.
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 Spring 2026 Cohort)
Step 1
Read Future Scholar Prospectus
Attend Information Session
Step 2
Create Account on CCIR Admissions Portal
Submit Application
Choose from the research courses offering this round.
Submit your spring application before the Early Admissions Deadline of March 1, 2026, or Regular Admissions Deadline of March 15, 2026.
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 week after application submission.
Step 4
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 1-2 weeks after the applicant’s research course selection is submitted.
The tuition is expected to be complete in full within 5 business days after receiving the official offer as a confirmation of enrollment.
How to Apply (Pre-Application to Summer 2026 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 Summer pre-application before the Pre-Application Admissions Deadline of April 1, 2026.
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 April 1, 2026
Conditional offer holders will receive an invite to register their research course preference on March 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)
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 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 and Future Entrepreneur 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.
In the age of big data, a growing amount of research in the sciences is actually conducted outside of the lab context. Large amounts of data already exist and what is needed is for researchers to mine that data for insights. Our mentors will teach you the skills and tools needed for scientific computing and data analysis.
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
