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experimental data and workflows. The team drives innovation in algorithm design, GPU-accelerated computing, and quantum-ready methodologies applicable to complex scientific problems across the experimental
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-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity to apply a recently published, "proof-of-concept" method for synthetic enhancer design to a critical
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addition, computing time on national centers (GENCI) is allocated for this project. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5182-NATGIL-001/Candidater.aspx Requirements Research
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2027 - 03:31 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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required to maintain a new GPU cluster at KMI, spending no more than 20% of the FTE. The anticipated starting date is between April 2026 to October 2026. The appointment will be initially 2 years and may be
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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between INRIA and LJLL which focuses on high performance scientific computing. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7598-PIETOU-006/Candidater.aspx Requirements Research
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20 Feb 2026 Job Information Organisation/Company University of Jyväskylä Research Field Chemistry » Computational chemistry Chemistry » Other Computer science » Programming Computer science » Other
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 2 months ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Starting date: 01.04.2026
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significant computational component in deploying multi-GPU codes to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would