Cardiovascular Science: Technology and data-driven solutions

Doctoral Training Centre Degrees

Course code: RF_1

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The DPhil in Cardiovascular Science (Technology, Artificial Intelligence, and Data Driven Solutions for Cardiovascular and Metabolic Diseases) is a collaboration between the University of Oxford and Imperial College London.

The course is divided into two parts. In year one you will receive theme-specific multi-disciplinary skills training and complete two short projects linked to the DPhil project. In years two to four you will complete your DPhil project.

Year one

You will complete a 6-week, full-time (5 days a week) taught induction programme. This will be delivered through a combination of in-person and online sessions. Teaching will be led by a multi-disciplinary faculty spanning biomedical sciences, statistics, computing, engineering, and clinical medicine. You will be exposed to core areas where the department seeks to undertake transformative collaborative research, such as arrhythmias, heart failure, cardiomyopathies and atherosclerotic cardiovascular disease. You will also be taught core principles of artificial intelligence, data science, machine learning, and cardiovascular engineering, with a focus on multimodal data including imaging, wearable technologies, ECG and Holter monitoring, omics, and electronic health records.

A key component of the programme will be the use of real-world case studies, enabling you to apply these approaches to clinically relevant problems in cardiovascular disease.

Following this induction period, you will transition directly into your research projects relevant to your DPhil. You will work on an initial project with your Oxford supervisor (Jan-April / months 1 to 4) and a second project in collaboration with your Imperial co-supervisor (May-August/September / months 5 to 8/9).

These projects will form part of a single DPhil project, with formative assessments and opportunities for joint supervision, structured training, and cohort-based learning. This early start enables rapid development of research skills and close integration with ongoing projects. Where appropriate, projects may involve collaboration with industry partners, providing exposure to translational research and real-world implementation.

For the remainder of year one, following a modular framework overseen by the doctoral training programme (DTP)-team, you will then engage in local supervisor-led project-specific training, dovetailed with selected taught components from established courses at Oxford and Imperial.

Your bespoke training plan, co-developed with your supervisors, will be developed early in the programme in discussion with your supervisors and reviewed by the DTP team. Using this model, you will receive further tailored training relevant to your projects in year one (eg in computer programming, development of AI models, computational modelling, genomics/-omics, cardiovascular imaging analytics).

Additional sessions will cover research ethics, implementation science, public engagement, and enterprise skills.

You will also participate in cohort-based activities at Imperial College London, including interdisciplinary workshops, case-based discussions, and seminars, fostering a collaborative and supportive learning environment. This combination provides a strong foundation for interdisciplinary research and future career development.

Years two to four

In years two to four, you will continue to develop and deliver your main DPhil project, building on the foundations established during year one. You will benefit from ongoing supervision across Oxford and Imperial, alongside advanced training opportunities, interdisciplinary collaboration, and continued engagement with academic, clinical, and industry partners.

Taught courses

You will begin with a six-week induction programme spanning:

biomedical sciences
statistics
computing
engineering
clinical medicine
AI
data science
cardiovascular engineering.

Project training

You will receive project-specific training, dovetailed with selected taught components from established courses at Oxford and Imperial. These taught components will include:

Core principles of cardiovascular disease
Artificial intelligence, data science, and machine learning
Multimodal data analysis (imaging, wearables, ECG and Holter monitoring, omics, EHR)
Experimental design, research methods, and reproducible science
Case based learning using real world datasets
Research ethics, implementation science, and public engagement
Innovation, entrepreneurship, and industry engagement

Research areas

Themes

You will have the opportunity to undertake research within the specialised themes of this course, which include:

Cardiovascular disease prevention, treatment, and management
Artificial intelligence and data science in healthcare
Multimodal data integration (including imaging, ECG, wearable technologies, omics, and electronic health records)
Digital health and remote monitoring
Translational and data driven healthcare innovation

Research Project

During the first year, you will work on two projects relevant to your DPhil:

an initial project with your Oxford supervisor (Jan-April / months 1 to 4),
a second project in collaboration with your Imperial co-supervisor (May-August/September / months 5 to 8/9).

These projects will form part of a single DPhil project, which you will undertake during years two-four.

Supervisors

The following researchers are affiliated with this programme

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