Research Fellow in Computational Cardiovascular Flows, Mechanics and Devices (EPSCP1096)

Are you an early or mid-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 and 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?

We are looking for a Research Fellow 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.

You will hold a BSc/MSc (or equivalent) degree in relevant areas (i.e. physics, engineering, computer sciences, mathematics, or statistics), and a PhD (or have submitted your thesis before taking up the role) in a relevant computational domain. A track record in research commensurate with level of experience; in depth knowledge in statistics, physics, machine learning, and/or engineering and maths in the broad sense and proficiency in computer programming is a must. Experience in medical imaging physics and analysis (e.g. MRI, CT, and US) and a good knowledge in statistics and/or Bayesian learning would be advantageous.

What we offer in return

25 days holiday plus 15.5 Bank Holidays/days that the University is closed by custom (including Christmas) – That’s over 40 days a year!Health and Wellbeing: including options for flexible working, discounted access to our state-of-the-art Campus gym and sports facilities, and more. Access to on-site childcare, shopping discounts and travel schemes are also available.Personal Development: Access to courses run by our Organisational Development & Professional Learning team and self-development courses.A large but compact university campus housing state-of-the-art research facilities, transformational research, and a bustling innovation hub.

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

Email: A.Frangi@leeds.ac.uk

Closing Date: 06 Jun 2022

Section: Research

Salary: £34,304 to £40,927 p.a.
Due to funding restrictions, an appointment will not be made higher than £36,382 p.a.