4 Post-doc Positions in Physics Informed Learning and Deep Learning in Medical Imaging, University of Leeds, UK
Alejandro Frangi
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
Sincerely
Alex
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
Scientific
Director, Leeds Centre for Responsive
HealthTech Innovation
Director Research & Innovation, LIDA Leeds Institute of Data Analytics
The University of Leeds | Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom