Research Fellow in Image-based Computational Modelling in Cardiology University of Leeds, Faculties of Engineering and Medicine & Health United Kingdom

Are you an early-career researcher who enjoys finding solutions to challenging problems in translational biomedical engineering? Do you have a background in medical image computing and experience with working collaboratively with clinicians and clinical image databases? Do you have a passion for combining computational algorithms, modelling and simulation to address key problems in virtual in silico trials? Are you ready to think out-of-the-box, innovate and find solutions to challenging problems?

The Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), within the Faculties of Engineeringand Medicine & Health, involves various academics and their research groups. CISTIB focuses on algorithmic and applied research in the areas of computational imaging, and image-based computational physiology modelling and simulation. CISTIB contributes in different areas of medical image computing and image-based biomechanical and computational physiology modelling. CISTIB works in close cooperation with clinicians from various research centres from the University of Leeds and the academic hospitals of the Leeds Teaching Hospital Trust Foundation, the largest NHS Trust of the UK. 

Clinical areas where CISTIB members have contributed to and made substantive innovations in the field are focused around the cardiovascular, musculoskeletal and neural systems, where they have developed diagnostic and prognostic quantitative image-based biomarkers and methods and systems for interventional planning and guidance. The centre hosts academic members from the University of Leeds and Research Fellows, Research Associates, PhD Students and Scientific Software Developers forming a cross-disciplinary team committed to clinical translation of their innovations.

You will be part of the InSilc project, where CISTIB in collaboration with groups across Europe seeks to develop an in-silico clinical trial platform for designing, developing and assessing drug-eluting bioresorbable vascular scaffolds (BVS). Using your knowledge of image analysis and computation (covering topics like image registration, statistical models, and centreline models), you will contribute to the development of methods for highly-automated and robust construction of image-based models of the coronary vasculature and the simulation of coronary flow dynamics. You will contribute technical and scientific developments that fulfil the project objectives.

To explore the post further or for any queries you may have, please contact: 

Professor Alex Frangi, Diamond Jubilee Chair of Computational Medicine

Tel: +44 (0)113 343 5430 or email: a.frangi@leeds.ac.uk 

 

Further information

The Faculty of Engineering is proud to have been awarded the Athena Swan Silver Award from the Equality Challenge Unit, the national body that promotes equality in the higher educ


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