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This DPhil, which includes funding support from the British Heart Foundation (BHF), is for graduates who want to undertake advanced research into cardiovascular disease in Oxford.

The DPhil in Cardiovascular Science (Cardiovascular Disease Prevention) is a collaboration between the University of Oxford, the University of Cambridge, the University of Edinburgh, and Imperial College London.

This four-year DPhil course combines interdisciplinary training with in-depth research. 

You 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, you 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. You 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.

Course structure

An overview of the course structure is provided below. Details of the compulsory and optional elements of the course are provided in the Course components section of this page.

Year one

In year one, you will undertake training courses and research rotations (at your host institution) before selecting your DPhil project and supervisory team.

Years two to four

In years two-four, you will carry out your DPhil 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 
  • Flagship Pioneering.

Core Components

This programme combines interdisciplinary training with in-depth research. In year 1, you will undertake training courses and research rotations (at your host institution) before selecting your DPhil project and supervisory team. In years 2-4, you will carry out your PhD research with interdisciplinary supervision.

Training

Throughout the first year, students participate in a shared training programme including:

  • Ethical AI and Open Science
  • Patient and Public Involvement and Engagement (PPIE)
  • Scientific writing and communication
  • Leadership and professional development
  • Entrepreneurship and innovation.

Programme-wide academic activities include:

  • Student-led journal clubs
  • Cardiovascular research colloquia
  • Core skills workshops
  • PhD symposia bringing together the full cohort.

These activities foster interdisciplinary exchange and cohort development across institutions. These training areas are indicative and are subject to minor change.

Students also undertake structured training in data science and artificial intelligence, progressing towards advanced Master's-level knowledge.

Training modules draw on existing courses across the partner universities, enabling students to develop skills aligned with their research trajectory.

Students also pursue specialist training relevant to their developing research interests, which may include areas such as:

  • Imaging
  • Genomics
  • Systems biology
  • Bioinformatics
  • Epidemiology
  • Clinical trials
  • Computational methods.

These modules are drawn from existing Master's-level courses across the consortium institutions.

 

Research areas

Themes

All students, regardless of disciplinary background, will gain grounding in the programme’s three core domains:

  • Population health
  • Systems biology
  • Data science and artificial intelligence.

Research Rotations

During the first year, students undertake two research rotations, each lasting approximately ten weeks.

The aims of the rotations are to:

  • expose students to different scientific approaches
  • provide experience working with different supervisors
  • build interdisciplinary confidence
  • inform the choice of PhD project.

Rotations typically involve analysing multimodal data and working across disciplinary boundaries.

Research Project

The process of selecting a DPhil project and supervisory team takes place during months 4–9 of the first year. The programme adopts a student-centred approach, enabling students to play an active role in shaping their research trajectory.

Students are encouraged to refine potential projects with supervisors based on:

  • Interests emerging from research rotations
  • Training undertaken during the first year
  • Interdisciplinary opportunities within the consortium

You will undertake your main DPhil research project during years two-four. 

How to apply

Start date: October 2026 To apply, please email ps.phdadmin@medschl.cam.ac.uk with the following documents.

· Curriculum vitae (CV)

· Two letters of recommendation from your referees

· A cover letter (maximum 500 words) 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.

Application deadline: 16th April 2026

Supervisors

The following researchers are affiliated with this programme

Louise Bowman

Professor of Medicine and Clinical Trials, and Honorary Consultant Physician ...

Fiona Bragg

Associate Professor

Richard Bulbulia

Associate Professor, Clinical Trial Service Unit and Epidemiological Studies ...

Jonathan Emberson

Professor of Medical Statistics and Epidemiology

Ben Lacey

UK BIOBANK

Sarah Lewington

Professor of Epidemiology and Medical Statistics