Imperial College London
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Fully Funded PhD in Multimodal Foundation Models and Agentic AI for Heart Rhythm Disorders Imperial College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
The 3-year PhD studentship is fully funded by the National Heart and Lung Institute and provides a stipend plus Home tuition fees for three years. Tuition funding requires Home fee status.
Deadline
Jan 15, 2027
Country
United Kingdom
University
Imperial College London
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About this position
This PhD opportunity focuses on developing multimodal foundation models and agentic artificial intelligence for heart rhythm disorders at Imperial College London.
The project will combine electrocardiograms, electronic health records, clinical free text and medical imaging. The research will investigate foundation models, multimodal fusion, large language models and agentic AI, including AI co-scientist approaches that support multiple stages of the research process.
The student will work within a cardiovascular AI team connected to the National Heart and Lung Institute and the Imperial BHF Centre of Research Excellence. The wider research environment brings together practising clinicians, cardiac electrophysiologists, data scientists and engineers across Imperial and international collaborators. The programme offers access to data from more than 11 million people across eight or more countries, supporting research aimed at real-world impact in cardiovascular medicine.
Supervision will involve Fu Siong Ng, James Ware and Declan O'Regan, alongside a practising cardiac electrophysiologist with hands-on coding experience. The project is designed for researchers interested in applying advanced computer science and biomedical AI methods to clinically important heart rhythm problems.
The advert states that the studentship starts in October 2027.
Funding details
The 3-year PhD studentship is fully funded by the National Heart and Lung Institute and provides a stipend plus Home tuition fees for three years. Tuition funding requires Home fee status.
What's required
Applicants should be graduates with a Master's degree in computer science, artificial intelligence, engineering, biomedical sciences or a similar field, with strong Python and deep learning skills. Cardiology experience is not required. Home fee status is required for the stated tuition-fee funding.
How to apply
The advert is expected to follow, with interviews beginning in November. Interested candidates should monitor the forthcoming advert and apply early; informal enquiries can be sent to Arunashis Sau via LinkedIn.
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Professors
Professor
United Kingdom
Research Interests
Medical Imaging
Large Language Models
Deep Learning
Biomedical Engineering
Computer Science
Professor
United Kingdom
Research Interests
Cardiology
Biostatistics
Medical Science
Cardiomyopathy
Cardiac Pathology
Professor
United Kingdom
Research Interests
Medical Imaging
Biomedical Engineering
Electronic Health Record
Medical Science
Electrocardiography
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.