Research Associate in digital twin modelling for thrombosis risk predication in City of Westminster

The post holder will join a team of researchers to develop innovative and scalable cardiovascular digital twins for personalised cardiovascular care. The work will focus on novel strategies to integrate multi-modal patient datasets (including EHRs, imaging, lab tests) with population-level prior information, enabling a scalable digital twin to predict risks of developing thrombosis, with the long term vision of supporting a precision approach to anticoagulation therapy.

Main responsibilities

• Develop a digital-twin framework for modelling mechanisms of blood coagulation in two different type of patients (atrial fibrillation and coronary heart disease)
• Develop and benchmark probabilistic kernel-based and deep-learning surrogates to rapidly infer time-dependent thrombosis biomarkers from imaging, haemodynamic and blood data, with quantified uncertainty and robust generalisation to unseen anatomies.
• Integrate the digital twin with probabilistic Bayesian frameworks and derive population-level prior models from representative cohorts and primary care data.

Essential criteria

• PhD in biomedical engineering, computer science, applied mathematics, computational science, physics or a related discipline.
• Strong scientific programming skills, preferably in Python and/or C++.
• Demonstrable expertise in at least two of the following: biophysical computational modelling using commercial software (ANSYS), Gaussian-process emulators, deep learning models, neural and hybrid physics-informed models.
• Experience with medical imaging data processing (e.g. segmentation).
• Ability to undertake independent quantitative research and work effectively within a multidisciplinary team.

Desirable criteria

• Experience with multi-modal patient data curation and preparation.
• Experience with healthcare foundation models.
• Understanding of Bayesian inference and Bayesian personalisation methods.

King's College London is an internationally renowned university delivering exceptional education and world-leading research. The school of Biomedical Engineering & Imaging Sciences (BMEIS) at King's College London is a world-leading centre for transformative research at the intersection of engineering, medicine, and data science, which brings together cutting-edge technology, clinical expertise, and interdisciplinary innovation.

We are recruiting a Postdoctoral Research Associate (PDRA) to work on a 3-year EPSRC-funded project on developing a probabilistic digital twin framework for efficient, dynamic prediction of thrombogenesis risks in cardiovascular diseases. The role will be based within the Research Department of Digital Twins in Healthcare, part of the School of Biomedical Engineering & Imaging Sciences, King's College London. The Department is located within St Thomas' Hospital, one of the largest medtech research facilities embedded within an NHS hospital. They will work in an established, diverse group bringing together expertise in cardiovascular digital twins, artificial intelligence, computational modelling and clinical research., At King's, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great strengths of the university.

This is a full-time post (35 hours per week), and you will be offered a fixed term contract until 18th October 2030. Research staff at King's are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the for more information.

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