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Field
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
. Opportunities may also exist to participate in planned field campaigns in Greenland. The postdoctoral scholar will be expected to improve on existing GPU-accelerated ocean models and develop laboratory
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and work together to train models, architect systems, and run trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster
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numerical solvers for 2D and 3D phase field models Develop HPC-ready simulation pipelines for large-scale rupture and fracture-fluid systems Optimize performance for modern architectures including GPUs and
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NASA's Jet Propulsion Laboratory, focused on developing a next-generation, GPU-based climate model that learns physics from data to improve the accuracy of its projections. Will collaborate with
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Jet Propulsion Laboratory, focused on developing a next-generation, GPU-based climate model that learns physics from data to improve the accuracy of its projections. Will collaborate with oceanographers
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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
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 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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astrophysical free boundaries. Responsibilities include running high-resolution GPU-accelerated simulations on exascale computing systems, developing and applying geometric measure theory tools to quantify
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algebra methods targeting large-scale HPC systems. Optimization of linear algebra libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications