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libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications and machine learning. Integrate and benchmark the GINGKO library, a sparse solver
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grid analytics, and scientific imaging. The successful candidate will design and implement sparse algorithms for large-scale scientific and numerical computations. This role offers an exceptional
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Computer Science, Applied Mathematics, Physics, Computational Biology, Neuroscience with Computational or Theoretical focus, or a closely related field. Preferred Qualifications: Familiar with Information Theory
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The Robot Learning Lab in the Department of Computing at Imperial College London is seeking a talented Research Assistant (pre-doc) for an ambitious new project on dexterous robot learning. In
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program of independent research with the primary goal of improving the algorithm codes used to characterize the Earth’s gravitational field. Duties will include specialized scientific/numerical analysis
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https://scholar.google.com/citations?user=9IRAYdEAAAAJ& ;hl=en and https://www.physics.sjtu.edu.cn/amgg/ Research profile: Candidates with a previous background on GPU computing are especially encouraged
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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Sign In Create Profile Postdoctoral Research Associate-Computer and Information Research Tucson, AZ, United States | req23101 Apply Now Share Save Job Posted on: 6/11/2025 Back to Search
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methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
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buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value