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British Heart Foundation Imperial-Oxford 4-year Multidisciplinary PhD Program 2026: Technology and data-driven solutions for effective prediction, prevention and management of cardiovascular disease

Imperial College London Multidisciplinary / Cardiovascular Technology and Data Science
✓ Fully Funded ⏰ Closing Soon 🎓 Artificial Intelligence 🎓 Biomedical Engineering 🎓 Cardiovascular Science 🎓 Data Science 🎓 Digital Health 🎓 Medical Imaging 🎓 Omics 🎓 Precision Medicine 🎓 Remote Monitoring 🎓 Wearables phd AI Imperial College London University of Oxford biomedical research cardiovascular disease data-driven health digital twin fully funded multi-modal data predictive models wearable sensors

Call for applications for the 4-year British Heart Foundation Imperial-Oxford PhD studentships (October 2026) on technology and data-driven solutions for prediction, prevention, and management of cardiovascular disease.

Project Description

This program combines Imperial College London and University of Oxford to provide interdisciplinary PhD training. Students will work on large-scale multi-modal data, AI, and emerging technologies to transform cardiovascular disease prevention and management. Training includes: Developing and validating AI models using ECG, imaging, -omics, wearables, and EHR data Building digital twin simulations Working with biosensors and remote monitoring tools Developing novel engineering-based solutions for disease monitoring and treatment Students will gain hands-on experience with large datasets and integrated care records, supported by machine learning pipelines. PhD projects are aligned to program ambitions and will be available for allocation/selection in year one.

Entry Requirements

Strong academic background (Bachelor/Master’s in relevant field)

Interest in AI, biomedical engineering, computational biology, or data science applications in cardiovascular research

Ability to work in a multidisciplinary team

How to Apply

Send the following via email to m.zak1@imperial.ac.uk
:

CV

Names and addresses of at least two academic referees

Personal statement (max 1,000 words) explaining your interest

Selected candidates may receive a campus tour. Applicants should assume non-selection if no response is received within one month of closing date.

Eligibility

UK/Home
EU
International

Supervisor Profile

PF
Prof. Fu Siong Ng
Imperial College London, Multidisciplinary / Cardiovascular Technology and Data Science

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