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Field
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The Department of Computing wishes to recruit a Cloud and GPU Infrastructure Manager to be responsible for the administration, maintenance, and optimization of both our internal GPU infrastructure
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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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managing and administering an NVIDIA DGX SuperPod instrument. You and another HPC administrator will partner closely with a team of data scientists from Stanford Data Science to ensure that the GPU cluster
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Location: South Kensington Campus About the role: Applications are invited for the above post to work with Professor Christos Bouganis and his team at Imperial College London for a project funded by the Commission of the European Communities. The successful candidate will be integral to...
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-procedure-unit-gpu-30hrs Return to Search Results
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Serve as the Lead for the team ensuring smooth operation of the Linux cluster consisting of 300+ GPU/CPU compute nodes including parallel filesystems and high-performance network. This is partly
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rendering into medical imaging workflows. A major focus will be on accelerating inference and training using GPU-optimised components, including custom CUDA kernels. This role offers a unique opportunity to
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to benefit from latest advances in hardware technologies the ICON model was ported to run on Graphics Processing Units (GPUs) and is one of the first model that can be used in production
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metrics and usage statistics, identify inefficiencies on different levels (CPU/GPU, I/O patterns, etc.) and provide corresponding reports. You will work closely with researchers and HPC users and provide
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computing resources, with additional support involving HPC systems such as configuring GPU nodes, managing Slurm queues, containerising teaching notebooks, and enabling advanced pipelines Promote Robust