117 parallel-computing-numerical-methods "Institute of Computer Science" positions at EPFL
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Physics, Optics, Micro-/Nanotechnology, Materials Science, Energy, or a related quantitative field A strong background in several of the following fields: theory of light-matter interaction, computer
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formal verification with Lean You have experience AI-assisted theorem proving or algorithm discovery is an asset You have working knowledge of numerical analysis, ideally numerical methods for PDEs You
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shape the future of advanced computing and AI infrastructure at EPFL, one of Europe’s leading science and technology institutions. You will work with outstanding team members and researchers, cutting
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outstanding candidates working in formal methods and/or computer systems with interests in one or more of the following areas: machine-checked verification of systems software, GPU kernel semantics and
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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than
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user communities Profile Higher degree in computer science or education deemed equivalent; experience in the field Excellent technical knowledge of systems programming, and strong programming ability in
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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than
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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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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than
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be developing new methods for remote sensing. Profile PhD in Computer Vision Background in Computer Science Research experience in 3D Computer Vision, remote sensing and aerial imagery Strong