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part of the core PLI team, which includes top-tier faculty, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to
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-wave and multimessenger signals and to explore challenging regimes of parameter space. Unit URL https://www.uidaho.edu/science/academics/physics Position Qualifications Required Experience Demonstrated
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samples. Optimize reconstruction algorithms for efficient large-scale 3D imaging, including high-performance and GPU-accelerated computing where appropriate. Design, optimize, and validate a refractive
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of thick and strongly scattering samples. Optimize reconstruction algorithms for efficient large-scale 3D imaging, including high-performance and GPU-accelerated computing where appropriate. Design, optimize
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environment spanning computational chemistry, cell biology, physics, and materials science. The work will leverage GPU computing on high-performance supercomputers such as Saga and LUMI to accelerate drug
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Week 41.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 4403-26147 Is the Job related to staff position within a Research Infrastructure? No
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inhibitors with improved efficacy The project offers a highly interdisciplinary research environment spanning computational chemistry, cell biology, physics, and materials science. The work will leverage GPU
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biology results The project offers a highly interdisciplinary research environment spanning computational chemistry, neuroscience, molecular biology, and psychology. The work will leverage GPU computing
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D