26 computer-science-"https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral research jobs at EPFL
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international working environment Competitive salary and excellent working conditions – more information can be found on our website (https://www.epfl.ch/campus/services/human-resources/en/basic-starting-salary
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. Main duties and responsibilities The Kim Laboratory at the École Polytechnique Fédérale de Lausanne (EPFL) ( https://www.epfl.ch/labs/upkim/ ) is seeking a highly motivated postdoctoral researcher to
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Intelligence in Molecular Medicine (AIMM) Lab, led by Prof. Charlotte Bunne at EPFL, sits at the interface of computer science and the life sciences, affiliated with both the School of Computer and
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General The Artificial Intelligence in Molecular Medicine (AIMM) Lab, led by Prof. Charlotte Bunne at EPFL, sits at the interface of computer science and the life sciences, affiliated with both the
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Artificial Intelligence in Molecular Medicine (AIMM) Lab, led by Prof. Charlotte Bunne at EPFL, sits at the interface of computer science, artificial intelligence, and biomedical applications. The lab is
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. Candidate profile Applicants should have a PhD in biomedical engineering, electrical engineering, computer science, data science, computational neuroscience, human movement science, psychophysiology
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verified formally. You will publish and present your work internationally. You are the ideal candidate if You hold a PhD in mathematics, computer science or a related field You have a strong background in
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physics, engineering, computer science, or a related field. Strong scientific programming in Python and experience with GPU processing of large-scale datasets. Experience with inverse problems and 3D
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facilities around the world. Profile We are looking for a person with: PhD in physics, engineering, computer science, or a related field. Experience with inverse problems and 3D reconstruction methods
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management and in computer architecture domains, our ability to analyze data still falls behind the unstoppable data collection rates. Data-intensive applications are increasingly more demanding in