|Salary:||£28,762 to £34,308|
|Placed On:||9th February 2023|
|Closes:||16th February 2023|
Are you an early-career researcher who wants to set the theoretical foundations that solve clinical and industrial problems? Do you have a background in computational fluid dynamics, modelling medical device-tissue interactions, computational multi-physics or multi-scale modelling? Are you willing to take up the challenge of working across disciplines and on real-world data? Are you passionate for combining computational algorithms, modelling and simulation in trailblazing research to deliver in-silico trials of medical devices?
The Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), within the Faculties of Engineering & Physical Sciences and Medicine & Health, involves various academics and their research groups. CISTIB focuses on algorithmic and applied research in the areas of computational imaging, machine learning, deep learning, and computational physiology modelling and simulation. CISTIB works in close cooperation with clinicians from various research centres from the University of Leeds and the academic hospitals of the Leeds Teaching Hospitals NHS Trust, one of the largest NHS Trusts in the UK.
We are looking for a Research Assistant to support our work by developing high fidelity models of cardiovascular fluid dynamics and device-flow interactions through multi-physics, physiological modelling. Experience in developing efficient schemes to run ensembles of virtual experiments through accelerated numerical solvers and physics-informed machine learning is a bonus. We have identified cardiovascular medical devices as the first exemplar scenario with an emphasis on valvular prostheses.
Holding a BSc/MSc (or equivalent) degree in a relevant area (i.e. physics, engineering, computer sciences, mathematics or statistics); you will be proficient in computer programming (e.g. Python, MATLAB, C/C++, ANSYS, Abaqus, FreeFEM).
What we offer in return:
And much more!
To explore the post further or for any queries you may have, please contact:
Professor Alex Frangi, Diamond Jubilee Chair of Computational Medicine
Type / Role: