• 4 Post-doc Positions in Physics Informed Learning and Deep Leaning in M

    From Alejandro Frangi@21:1/5 to All on Fri Jan 1 11:54:40 2021
    Dear colleague

    I’d appreciate it if you could circulate the post-doctoral job announcements below amongst interested candidates. Deadline is Jan 8th 2021.

    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 computer vision, medical image computing, machine and deep learning, biomedical engineering
    or computational multi-physics and multi-scale modelling? Are you willing to take up the challenge to working across disciplines and on real-world data? Are you passionate for combining computational algorithms, modelling and simulation in trailblazing
    research to create virtual patient populations and deliver in-silico trials in medical devices?

    This is an exciting opportunity to join a 10-year programme funded by the Royal Academy of Engineering on Emerging Technologies



    Research Fellow in Deep Learning in Medical Image Computing & Modelling (Up to 2 posts) https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSCP1030

    Research Fellow in Computational Cardiovascular Flows, Mechanics & Devices (Up to 2 posts) https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSCP1029



    Prof Alejandro F Frangi, FIEEE, FSPIE, FEAMBES

    Diamond Jubilee Chair in Computational Medicine

    Royal Academy Chair in Emerging Technologies

    School of Computing | School of Medicine, University of Leeds, United Kingdom

    Department of Electrical Engineering | Department of Cardiovascular Sciences, KU Leuven, Belgium
    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)