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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 5 hours ago
. Bert de Groot) is inviting applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations
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computing and machine learning. The research will emphasize both theoretical advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more
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that address real-world challenges and deliver positive business outcomes. The Institute for Insight is equipped with a computer cluster that includes multiple GPUs, designed for big data analytics for both
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
. Helmut Grubmüller) is inviting applications for a PhD Student or Postdoc (f/m/d) - Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules. Possible projects
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in physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the abovementioned fields. What we offer State of the art on-site high performance/GPU compute
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development. This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP
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well as an integral member of the AI Lab and the research community it supports. You will work with a diverse group of faculty, postdocs, and students from multiple disciplines. If you are passionate about advancing AI
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advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
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artificial intelligence. You will work with a diverse group of faculty, postdocs, and students from multiple disciplines, including cognitive science, psychology, computer science, statistics and machine
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provide a performance or efficiency advantage, and determine scenarios where conventional AI accelerators (such as embedded GPUs or FPGA-based accelerators) remain more appropriate due to data