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designing, operating , automating, and optimizing the GPU and AI and computing infrastructure used by resea rchers across the university , along with the high-performance computing systems that
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designing, operating , automating, and optimizing the GPU and AI and computing infrastructure used by resea rchers across the university , along with the high-performance computing systems that
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-performance computing, GPU-enabled environments, distributed or cluster-based systems, and AI infrastructure, along with experience developing or supporting computational platforms, research software, or
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problems involving very large mesh (tens and hundreds million) Skills in AI-enabled and GPU-based calculations are welcome Good communication skills and the ability to work in a team environment
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single-particle cryoEM and cryo-ET, and a Hydra FIB-SEM for in situ structural studies of cellular and tissue sections. The lab has multiple GPU workstations and access to the university computing
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Preferred skills/knowledge includes: Active TS/SCI Clearance Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial
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: Active TS/SCI Clearance Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data Statistics, multivariable
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and implemention deep neural networks, including CNNs, RNNs, or Transformer-based architectures Familiarity with training and evaluating models on GPU-accelerated hardware Ability to build