心血管研究预防方向BHF 4年制博士生

University of Cambridge, University of Edinburgh, Imperial College London and University of Oxford.

Applications are invited for 10 funded 4-year PhD studentships starting in October 2027, as part of the British Heart Foundation (BHF) doctoral training programme focused on preventing cardiovascular disease through innovative, data-driven approaches.

This interdisciplinary PhD programme brings together leading researchers from the University of Cambridge, University of Edinburgh, Imperial College London, and the University of Oxford. Students will be trained to work at the intersection of population health, systems biology, and data science/AI, combining expertise across these fields to tackle one of the most pressing challenges in global health. By harnessing large-scale multimodal data and emerging technologies, students will develop new approaches to understand, predict, and prevent heart and circulatory diseases.

Students will be based in one of the following institutes: Cambridge (5 studentships), Edinburgh (2 studentships), Imperial (1 Studentship) or Oxford (2 studentships) while benefiting from training, co-supervision, and collaboration across the partner institutions. Projects will span a range of topics including health data science, AI and machine learning, multi-omics, epidemiology, and translational cardiovascular research. Students will be part of a cohort-based programme, gaining access to shared training activities, collaborative networks, and state-of-the-art data resources across the multi-institute partnership.

This four-year PhD programme combines interdisciplinary training with in-depth research. In year 1, students will undertake training courses and research rotations (at their host institution) before selecting their PhD project and supervisory team. In years 2-4, students will carry out their PhD research with interdisciplinary supervision. Additional opportunities will include advanced training courses, programme-wide workshops and symposia, and optional placements 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 co-leads of the programme are: Cambridge - Professor Angela Wood

Edinburgh - Professor Nicholas Mills

Imperial - Associate Professor Michela Noseda

Oxford - Professor Sarah Lewington

Eligibility

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.

Applicants should also demonstrate strong analytical skills, experience working with data or computational methods, and an interest in interdisciplinary research. Strong communication and teamwork skills are essential, and international applicants may need to provide evidence of English language proficiency.

Funding

The studentship provides:

• University tuition fees (UK home rate only)

• A tax-free stipend at the BHF rate

• Research training and support

We invite applications from students who meet the UK residency requirements (home fees). International students who confirm that additional costs of all overseas tuition fees will be covered through other scholarships or funding schemes will also be considered.

How to apply Please do not use the University application portals.

To apply, please email bhfphdadmin@medschl.cam.ac.uk with the following documents.

• Curriculum vitae (CV)

• Two letters of recommendation from your referees, signed

• Transcripts

• A cover letter (maximum 2500 characters) outlining your suitability for the PhD programme and indicating your preferred host institutions in order of preference. Please list only institutions that you would be willing to attend if offered a place, even if they are not your first choice.

• Evidence of competence in English - If required - please see our Competence in English guidance for more information.

AI must not be used when writing personal statements and CVs.

This prohibition covers the use of AI to help your use of English. Using AI in your application ' Postgraduate Study

https://www.postgraduate.study.cam.ac.uk/apply/how/ai-postgraduate-applications

Application deadline: 8th December 2026

Please quote reference RH51427 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.