Research Associate in Cardiovascular Digital Twins

Job description:

We are offering an exciting opportunity to build cardiovascular digital twins to improve patient care pathways. This role would enable you to be at the forefront of a project that will meaningfully improve patient outcomes with highly innovative technology. We are seeking candidates with a PhD and proven experience in python programming and code development. As this role involves working with knowledge graphs, you will also need experience/knowledge of graph modelling, ontologies and databases. Familiarity with neo4j, Flask, software containers and retrieval augmented generation would be an advantage.

Digital twins are virtual replicas that continuously assimilate patient data to provide personalised predictions and advise clinical decisions. This work is a collaborative project between Imperial College, Sheffield, Nottingham, The Alan Turing Institute plus others. The role is to develop networks of patient-based digital twins. The networks will enable us to develop new types of care pathways for pulmonary arterial hypertension. The post holder will collaborate with the interdisciplinary team to develop and implement networks of digital twins’ leading to time evolving digital threads.

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.

We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to the greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.

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