Cardiovascular Research PhD programme

This Cardiovascular Research PhD programme at University of Cambridge will train a new generation of researchers to tackle cardiovascular disease prevention by equipping a new generation of cross-disciplinary researchers to work at the intersection of three frontiers:

• Population health – analysing large-scale health data from diverse populations to understand disease risk and prevention
• Systems biology – studying the biological processes underlying disease across multiple levels, from cells to whole organisms
• Artificial intelligence and data science – developing computational methods to integrate and interpret complex biomedical data.

Key facts

The programme brings together leading scientists from the Universities of Cambridge, Edinburgh, Imperial College London and Oxford, working in partnership with our academic or industry partners, including EMBL-European Bioinformatics Institute, Wellcome Sanger Institute, AstraZeneca, Novo Nordisk, Genomics Ltd, Owlstone Medical, ThermoFischer Scientific and Flagship Pioneering.

The programme is designed to prepare students to work in collaborative, interdisciplinary environments, recognising that many of the most important advances in disease prevention occur where different scientific fields meet.

A key aim of the programme is also to advance research that benefits diverse and previously under-studied populations, helping to generate new knowledge that can reduce inequalities in cardiovascular health.

By combining interdisciplinary training with real-world collaboration, the programme seeks to equip students with the expertise and networks needed to become leaders in cardiovascular disease prevention research.

Programme Structure

Curriculum includes:

• The first year of the programme provides foundational training and research immersion designed to equip students with the knowledge, skills, and perspectives needed for interdisciplinary research in cardiovascular disease prevention.
• During this year, students will undertake a combination of training and exploratory research activities. This includes participation in programme-wide workshops, seminars and optional selected taught modules (e.g., drawn from existing Master's-level programmes) that provide grounding in the programme's core domains: population health, systems biology and data science/AI.
• From the second year onwards, students will focus primarily on their PhD research project. Projects will typically be co-supervised by researchers from different disciplines and may involve collaboration across institutions within the consortium.

Admission requirements

Academic requirements

• GPA – Upper Second Class

English requirements

• TOEFL iBT – 107
• IELTS – 7.5

Other requirements

General requirements

• Applicants for this course should have achieved a Good II.i Honours Degree.
• If your degree is not from the UK, please check International Qualifications to find the equivalent in your country.
• Applicants should hold, or expect to obtain, a first or upper second-class undergraduate degree (or equivalent) in a relevant discipline such as statistics, mathematics, computer science, data science, engineering, bioinformatics, epidemiology, biomedical sciences, genetics, public health, or another quantitative or biomedical field, and may also hold a Master's degree in a related subject.
• Two referees willing to give you a reference. Either academic or professional. Your referees will need to have submitted their reference by the course deadline.
• Transcript
• CV/resume
• Evidence of competence in English
• Core - Statement of Interest (2500 characters) (mandatory)
• School of Clinical Medicine - Widening Participation Questionnaire

Fees and funding

Tuition Fees

Tuition fees are shown in AUD and the most likely applicable fee is shown based on your nationality.

• International: 80,328 AUD / year (≈ 42,546 GBP / year)
• Domestic: 21,161 AUD / year (≈ 11,208 GBP / year)

Living costs

Cambridge, United Kingdom: 1,597-2,766 AUD / month

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.