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EPSRC collaborative studentship: Predicting safe same-day safe-discharge in patients following a Transcatheter Aortic Valve Implantation (2026)

What you get

As an EPSRC student you will join a vibrant doctoral community and will benefit from 3.5 years of funding with a tax-free living allowance at the standard Research Council rate (currently £20,780 in 25/26), UK tuition fees, and funding for training and research expenses, such as conference trips and experimental costs.

Type of award

Postgraduate Research

Funding type

Partnership

PhD project

This interdisciplinary PhD project, co-funded by medical device manufacturer Edwards, will develop trustworthy, interpretable machine learning tools to guide patient care following Transcatheter Aortic Valve Implantation (TAVI). The student will be supervised by (Associate Professor in AI, Department of Informatics) and Dr Chris Broyd (Consultant Cardiologist, University Hospitals Sussex NHS Foundation Trust).

In this project, the student will adapt state-of-the-art machine learning methodologies to create models that take multi-modal pre-operative data (including CT imaging, ECG, and other biomarkers) to predict clinical measures and outcomes.  This is a computational project, which would suit a student with good mathematical and programming skills and a keen interest in medical imaging. Students will be expected to present their work at top-tier journals and conference in medical imaging or machine learning.

The role offers a unique opportunity for a computational researcher to work at the interface of AI and clinical practice, gaining first-hand experience with diverse medical data. The student will spend 1–2 days a week embedded at the hospital, ensuring they work closely with both the clinical and academic supervisors.

Keywords: Machine learning, medical image analysis, artificial intelligence, medical informatics

Eligibility

Applicants should have at least a 2:1 undergraduate honours degree in a relevant subject and meet our English language requirements.

Sussex recognises the value of diversity in research communities and is committed to addressing patterns of under-representation. We recognise that a range of factors, both structural and individual, influence and impede pathways into postgraduate research in different ways.  If you wish, you may write a short, optional statement offering any further contextual information affecting your pathway to postgraduate research not included elsewhere that you think is relevant to your application.

Deadline

14 November 2025 23:59

How to apply

1. Apply for a PhD place at Sussex using the online PhD application system.
2. Apply for the PhD course in INFORMATICS with JANUARY 2026 start date. State Prof Ivor Simpson as your preferred supervisor and enter “EPSRC” in the “sources of funding” box.
3. Upload as attachments your CV, degree certificates and transcripts and English language qualifications if applicable.

Contact us

For questions regarding the project, please contact the supervisor: i.simpson@sussex.ac.uk 

If you have questions relating to the online application process, please contact: fosem-pgr@sussex.ac.uk