Postdoctoral Research Associate in Image-based Vascular Modelling for AI and CFD in Digital Twin Assisted Surgery

You will develop patient-specific vascular models from medical images to drive AI and CFD approaches for next-generation surgical planning and intervention. This post sits within a large, multidisciplinary EPSRC-funded Transformative Healthcare Technologies project “Real-time Digital Twin Assisted Surgery” (Ref: EP/X033686/1, £4M), bringing together expertise in medical imaging, computational modelling, artificial intelligence, surgery and biomedical engineering.

In this role, you will lead the image-to-model framework, transforming clinical imaging data into high-fidelity 3D vascular geometries that underpin both data-driven (AI) and physics-based (CFD) digital twins. Your work will shape how personalised surgical strategies are simulated, optimised and ultimately translated into the operating theatre.

You will work closely with clinicians, AI researchers, computational modellers and biofabrication experts, and will be encouraged to lead methodological development, publish in high-impact journals, and contribute to the next generation of digital-twin-enabled surgery.

As a Research Associate, under the general guidance of a research leader, you will:

• Develop research objectives and proposals
• Play a lead role in relation to a specific project/s or part of a broader project
• Conduct individual and/or collaborative research
• Contribute to the development of new research methods
• Identify sources of funding and contribute to securing funds for research, including drafting grant proposals and planning for future proposals
• Write up research work for publication, individually or in collaboration with colleagues
• Disseminate results via peer-reviewed journal publications and presentations at conferences
• Join external networks to share information and ideas, inform the development of research objectives and identify potential sources of funding
• Collaborate with colleagues to ensure that research advances inform departmental teaching efforts
• Supervise student projects, provide advice to students and contribute to teaching as required
• Contribute to the Department, Faculty and/or University administrative and management functions and committees
• Engage in continuous professional development

To be considered for the role, you will be educated to a minimum of PhD level in an appropriate discipline, or have significant relevant experience in addition to a relevant degree. You will have sufficient breadth or depth of knowledge in vascular image segmentation, 3D vessel reconstruction, computational fluid dynamics (CFD), computer-aided design (CAD), morphing algorithms, fluid-structure interaction, Windkessel boundary conditions, 0D/1D-3D coupling, and a developing ability to conduct individual research work, disseminate results and prepare research proposals.

You will have an ability to plan and organise your own workload effectively and an ability to work within a team environment. You will have excellent interpersonal and communication skills, with the ability to listen, engage and persuade, and to present complex information in an accessible way to a range of audiences.

Whilst not essential for the role, applications are welcomed from candidates with relevant work experience, membership of relevant Chartered/professional bodies (including the Higher Education Academy), experience of relevant student supervision and teaching activities, and/or experience of knowledge exchange related activities.

Whilst a Post-Doctoral Research Associate is ideally sought for this position; applications from candidates who are close to PhD completion or whose award is pending, are welcome. In such circumstances, the appointment will be made at Research Assistant level (grade 6) and duties will be adjusted to reflect the grade of the post. This will continue until the PhD award is confirmed, at which point the duties and grade will be revised accordingly.