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- into a GPU-enabled and parallel code to run efficiently on state-of-the-art exascale hardware Designing implementations and reviewing community contributions of library features and new statistical
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, OpenFOAM), and plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 6 hours ago
hold a PhD or equivalent degree in the above mentioned or related fields. What we offer State of the art on-site high performance/GPU compute facilities A team of 30+ expert colleagues A family friendly
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on materials science tasks as well as integrate your semantic-AI services into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation Collaborate with
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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work
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into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation Collaborate with experimentalists and theorists to validate extracted knowledge via in
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
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environment with strong expertise in immunotherapies An open, collegial, and supportive working atmosphere in a respectful organizational culture A highly diverse and inclusive workforce Access to our GPU
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molecular dynamics simulations and was specially designed for parallelisation on GPUs. It is open source and licensed under the LGPL. Details can be found on the website https://halmd.org Job-Description