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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 6 hours ago
employment. Starting date: 01.09.2026 Job description:PhD Student (f/m/d) for HPC/GPU Computing With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 6 hours ago
systems research. The Department of Scientific Computing Core is looking for a Postdoc (f/m/d) GPGPU Computing. Your tasks # Research in GPU programming and (highly) parallel programming for HPC and
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can be switched on the network and can be consumed by the GPUs without additional overhead. Main activities: You will be part of the "Scientific Computing and Data Science" (CSSD ) team made up of 7
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. Computational Optimization: Resolving hardware-specific performance and numerical precision challenges across diverse GPU environments. Architecture Design: Leading the design of new loss functions, model
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Posting Number R260058 Posting Link https://www.ubjobs.buffalo.edu/postings/61964 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting
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national high-performance computing resources (Jean Zay). The position is based in Caen, a dynamic city located 2 hours from Paris. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6072-FREJUR0
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well as large-scale GPU computing facilities for deep learning. We are looking for a Research Engineer to manage the EEE GPU Cluster. The role will focus on enhancing the EEE GPU Cluster team’s ability in terms
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of three active research communities: operating systems memory management (NUMA policy, page migration, swap behaviour), high-performance and GPU computing (memory coalescing, unified memory, PCIe transfer
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orchestration in Kubernetes (e.g., NVIDIA device plugin, GPU scheduling, MIG, node affinity). Experience optimizing GPU utilization, memory management, and cost efficiency for compute-intensive workloads
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, MIG, node affinity). Experience optimizing GPU utilization, memory management, and cost efficiency for compute-intensive workloads. Preferred Competencies Ability to collaborate and interact effectively