The University of Sussex is offering a fully funded PhD position in Machine Learning and Cardiac Electrophysiology, focusing on advancing the mechanistic understanding of atrial fibrillation (AF) through analytical and physics-based machine learning. This EPSRC collaborative studentship is part of the Doctoral Landscape Award and involves collaboration with University Hospitals Sussex and an industry partner. The project aims to analyze dual-layer heart data to study interactions between the heart’s inner and outer layers, focusing on dissociation and its role in AF maintenance. It will develop machine learning models that incorporate physical properties of the heart to identify patterns and predict areas driving AF. The research combines advanced computational methods, experimental protocols, and clinical data, offering a unique opportunity to bridge machine learning, cardiac physics, and clinical practice. Applicants should have at least a 2:1 undergraduate degree in a relevant subject, with strong skills in mathematics, physics, and/or machine learning. No prior medical background is required. The studentship provides 3.5 years of funding, including a tax-free stipend (£20,780/year), full tuition coverage for UK or international students, and additional support for research expenses and placements. The application deadline is 16 June 2025, with a start date in Autumn 2025. To apply, contact Professor Luc Berthouze, prepare your application for the Informatics PhD program, and submit all required documents online. For further details, visit the Sussex scholarship page or contact the provided emails.

A fully funded PhD position is available at the University of Sussex, UK, focusing on advancing mechanistic understanding of atrial fibrillation through analytical and physics-based machine learning. This EPSRC collaborative studentship offers the opportunity to work with University Hospitals Sussex and an industry partner, combining machine learning, cardiac physics, and clinical data to address the complexity of atrial fibrillation (AF), the most common heart rhythm disorder. The project aims to analyze dual-layer heart data, study interactions between heart layers, and build machine learning models that incorporate physical properties to predict AF drivers. Applicants will join a vibrant doctoral community, benefit from research training, and have access to workshops and placements. The position is open to graduates with at least a 2:1 in a relevant subject and a strong background in mathematics, physics, or machine learning. No prior medical background is required. Funding includes a 3.5-year tax-free stipend (£20,780/year), full tuition coverage for UK or international students, and support for research expenses. The application deadline is 16 June 2025, with a start date in Autumn 2025. To apply, contact Professor Luc Berthouze, submit an online application for the PhD in Informatics, and upload the required forms and documents. For queries about the application process, email [email protected].