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learning for policy optimisation, all within a huge GPU-based simulation with thousands of robots learning synchronously in parallel. The best solutions will then be 3D-printed, and policies will be fine
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the Alps supercomputer at the Swiss National Supercomputing Centre (CSCS), which features over 10,000 NVIDIA Grace Hopper GPUs, making it one of the most powerful AI-focused computing resources in
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management of a state-of-the-art medical imaging research data center. The environment includes a robust multi-CPU/GPU architecture with virtual and physical servers, supporting advanced parallel computation
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Supercomputer Center which houses a 20 PFLOP CPU+GPU-capable machine. Application Requirements Document requirements Curriculum Vitae - Your most recently updated C.V. Cover Letter (Optional) Statement of
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is also the home of the Vermont Advanced Computing Center, a research facility with both high-performance CPU and GPU clusters. The Larner College of Medicine is a short (<5 minutes) walk from
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is also the home of the Vermont Advanced Computing Center, a research facility with both high-performance CPU and GPU clusters. The Larner College of Medicine is a short (<5 minutes) walk from
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of machine learning models Preferred skills/knowledge includes: A Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data
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software development with GPUs. Experience with visualization of large data sets. An understanding of how to make results easily available using common web interfaces. Required Documents Resume Cover Letter
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requirements. 7. Managing ESXi (Dell PowerEdge) server resources, including modification of RAM, GPU, CPU, Storage Disks when necessary to ensure uninterrupted service to the users. 8. Monitoring performance
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computing (HPC) systems, including GPUs, and programming, such as using CUDA, MPI, AI/ML/DL, and advanced debuggers and performance analyzers. Familiarity with working on open-source projects. About UF