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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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, turbulence, CFD, numerical methods, and turbulent combustion. • Proficiency in HPC environments (parallel computing on CPU/GPU systems) • Demonstrated publication record in reputable journals/conferences
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 3 days ago
with turbulence, flow control, scientific computing, or data-driven modeling. Experience with GPU computing and supercomputers is desirable. Good English skills. Additional information The position is
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collaborative, international team. We offer Cutting-Edge Resources: Access to state-of-the-art compute and GPU infrastructure, including H100 and B300 GPU clusters. Innovation: The opportunity
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bioimaging and bioinformatics team at IBENS, under the supervision of Auguste Genovesio. The postdoctoral researcher will have access to a workstation as well as computing servers equipped with GPUs. Where
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, Vehicular Communications Experience in system modeling and simulation of communication systems Strong programming skills in MATLAB are required; experience with Python, C/C++, or GPU-based computing is an
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provides high-performance GPU computing resources that support the design and training of advanced AI models. The research agenda of CVI2 focuses on cutting-edge topics such as 3D understanding and
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hardware architects to establish how agentic AI and these languages co‑design with heterogeneous HPC systems (CPUs, GPUs, PIM, AI accelerators). Study performance and portability tradeoffs, leveraging
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languages; experience with GPU programming (e.g., CUDA) is highly desirable. Background in optimization, image-guided radiotherapy, medical imaging, or computational modeling. Experience with treatment
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on small test clusters. Test computational performance and resolve technical challenges on significantly larger models of selected quantum materials. Work on speeding up Krylov solvers on GPUs. Demonstrate