24 high-performance-computing positions at Chalmers University of Technology in sweden
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the division and the research The Division of Subatomic, High-Energy and Plasma Physics performs research on theoretical and experimental subatomic physics, mathematical and high-energy physics, plasma
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research in theoretical laser plasma physics in a collaborative and dynamic environment. Information about the division and the research The Division of Subatomic, High-Energy and Plasma Physics performs
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Familiarity with optimization algorithms and design of experiments methodologies Experience with high-performance computing environments Track record of publications in peer-reviewed journals Previous
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methodologies Experience with high-performance computing environments Track record of publications in peer-reviewed journals Previous experience with Open Science practices (e.g. contributions to open-source
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participation in meetings and workshops. Your daily tasks will include coding scripts and performing computations using CFD, FEM, and acoustics software. Over the course of the position, you will gradually
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. The position involves regular communication with industry and research organizations, including participation in meetings and workshops. Your daily tasks will include coding scripts and performing computations
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Join the cutting-edge RAM³ project: Unlocking the Potential of Recycled Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics. We are offering a PhD position
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NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through machine learning, computer vision, and materials science. The focus of this position is on
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This multidisciplinary position is part of a WASP NEST (Novelty, Excellence, Synergy, Teams) project focused on advancing generative models and perceptual understanding in computer vision. The
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Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics” - a multidisciplinary research effort at the intersection of machine learning and materials science. This