Research Associate on Cardiac Digital Twins Part-time

Research Associate on Cardiac Digital Twins

We are looking for a postdoctoral research associate in AI-enabled cardiac modelling and simulation and digital twin technology at the Department of Computer Science. The post-holder will report directly to Professor Blanca Rodriguez and will work as part of the Computational Cardiovascular Science Team within the Computational Biology & Health Informatics research theme, collaborating closely with computational and clinical partners to translate cardiac digital twin technology towards clinical application.

The overall project aims to develop and clinically validate digital twins integrating cardiac imaging, electrocardiography, and computational modelling to enable personalised, non-invasive characterisation of cardiac function. The post-holder will develop and apply AI and physics-based computational methods for patient-specific cardiac digital twin generation, including image-based mesh construction, electrophysiological and mechanical model personalisation from clinical data, and will engage with clinical collaborators.

What we offer as an employer includes:

• An excellent contributory pension scheme
• 38 days annual leave (pro-rata for part-time roles)
• A comprehensive range of childcare services
• Family leave schemes
• Cycle loan scheme
• Discounted bus travel and Season Ticket travel loans
• Membership to a variety of social and sports clubs

The postholder will work onsite in the Department of Computer Science buildings in central Oxford, however remote (within the UK) and flexible working can be considered.

Committed to equality and valuing diversity.

Application process: You will be required to upload a supporting statement and an up-to-date CV as part of your online application. Your supporting statement must clearly demonstrate how you meet each of the essential selection criteria listed in the job description. Applications that do not include a supporting statement or CV, or fail to address the criteria in sufficient detail, will not be considered.

While we recognise the value of AI tools in assisting with application preparation, submissions that are clearly AI-generated without personalisation or insight will be rejected. It's crucial that your application reflects your own experiences and understanding of the role.

The closing date for applications is noon on Wednesday 19th August 2026.