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4 Post-doc Positions in Physics Informed Learning and Deep Leaning in Medical Imaging, University of Leeds,
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Alejandro Frangi
Jan 1, 2021, 2:54:42 PM1/1/21
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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
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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