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heterogeneous (CPU/GPU) computing models. Collaborate with physicists, computer scientists, mathematicians and engineers across LBNL divisions to define software requirements, implement robust solutions, and
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Job Code 0005 Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job The successful applicant will assist in the adaptation of the PPMstar code to run well on GPU-accelerated
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experiments, particularly ATLAS and DUNE. Contribute to the architecture and core development of the Phlex framework, emphasizing scalable, multi-threaded, and heterogeneous (CPU/GPU) computing models
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analysis systems using GPU- and FPGA-supported HPC clusters at large international research facilities such as Effelsberg, SKA, and MeerKAT. The systems developed by the BDG are based on state-of-the-art
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heterogeneous (CPU/GPU) computing models. Collaborate with physicists, computer scientists, mathematicians and engineers across LBNL divisions to define software requirements, implement robust solutions, and
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA INDUSTRIALE | Italy | about 1 month ago
Description Analysis and development of methodologies to accelerate the computation of numerical optimization through parallelization and the use of GPUs. Where to apply Website http://www.unibo.it Requirements
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• Execute large-scale simulations on CPU and GPU-based HPC clusters • Analyze results, generate technical reports, and deliver project outcomes on schedule • Prepare scientific reports and publish in
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international journals or conferences. Experience in predictive modeling for forecasting or recommendation systems. Strong programming skills in Python and AI frameworks (PyTorch, TensorFlow), including GPU/cloud
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and collaborative team of computational scientists, software and AI engineers, and neuroscientists, you’ll have access to high-performance workstations, CPU/GPU clusters, and experimental systems
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projects at CASS. The center fellows will have access to a 70,000-core Infiniband Cluster (Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities