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including knowledge of PyTorch, Tensorflow, Pandas, Scikit-learn and/or Numpy. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques. Fluency in spoken and written
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, TensorFlow) with several years of practice Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning
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Education Centers across Tennessee, providing real-world testbeds for agricultural technology deployment • State-of-the-art computing resources, including high-performance computing (HPC) clusters and GPU
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publications in peer-reviewed journals or conference proceedings, showcasing contributions to the advancement of HPC technologies. Specialized skills in specific areas of HPC, such as GPU programming, quantum
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together more than 400 researchers across disciplines. The collaboration provides access to substantial computational resources (GPU nodes), advanced high-throughput instruments (including a FACS, mass
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gun, associated diagnostics resources, and well-equipped high-speed and reacting flow laboratories. The National Center for Supercomputing Applications houses the most performant GPU-based systems and
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19,000 graduate students. The university is home to the HiPerGator 3.0 Supercomputer and HiPerGator AI, one of the most powerful GPU-enabled AI systems in U.S. higher education. The Department of Geography
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
. The postdoctoral scholar will be expected to improve on existing GPU-accelerated ocean models and develop laboratory experiments (in the Joint Fluids Lab at UNC), analyze results, publish in peer-reviewed journals
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at the Department of Informatics. Position as Postdoctoral Research Fellow available at the Department for Informatics with the research group Digital Signal Processing and Image Analysis (https://www.mn.uio.no/ifi
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Abilities: Experienced in heterogenous computing with GPU accelerators using one of the programming models: CUDA, HIP, SYCL, Kokkos, OpenMP, OpenACC and similar. Familiar with distributed parallel computing