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sci / sci.physics.computational.fluid-dynamics / 4 Post-doc Positions in Physics Informed Learning and Deep Leaning in Medical Imaging, University of Leeds,

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o 4 Post-doc Positions in Physics Informed Learning and Deep Leaning in Medical ImAlejandro Frangi

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Subject: 4 Post-doc Positions in Physics Informed Learning and Deep Leaning in Medical Imaging, University of Leeds,
From: Alejandro Frangi
Newsgroups: sci.physics.computational.fluid-dynamics
Date: Fri, 1 Jan 2021 19:54 UTC
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Subject: 4 Post-doc Positions in Physics Informed Learning and Deep Leaning in
Medical Imaging, University of Leeds,
From: alejandro.frangi@gmail.com (Alejandro Frangi)
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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

https://www.raeng.org.uk/news/news-releases/2019/april/royal-academy-of-engineering-awards-%C2%A320-million-in

https://fluid-dynamics.leeds.ac.uk/news/raeng-chair-in-emerging-technologies-awarded-to-cdt-supervisor-prof-alejandro-frangi/.

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

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