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Field
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, CUDA. B3 Knowledge of UK data protection laws and certification and accreditation schemes related to the processing of sensitive data for research. Skills Essential: C1 Excellent strategic leadership
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Computing (HPC) knowledge around cluster builds, software, parallel computing, workload management, and cluster management. Knowledge with CUDA Programming Workflows, GPU programming, and GPU support
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lattice field theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging
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using GPU/CUDA clusters for AI/ML and/or image processing. Proven ability to work in a dynamic environment and support large data systems. Effective documentation skills, including ability to prepare
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Linux kernel internals, computation accelerators (e.g., GPU computing, CUDA), MPI, and OpenMP. Highly resourceful and adept at juggling multiple simultaneous projects. Must demonstrate ability to work
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• Familiarity with operating HPC clusters (e.g., bash, Python) Preferred Qualifications • HPC programming skills (e.g., modern Fortran or C/C++) • Parallel programming skills (e.g., OpenMP, MPI, OPENACC, CUDA
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closure modeling and/or high performance computing environments (MPI, CUDA) • Expertise in software development and computing tools (C/C++, python, git, parallel computing, etc.) • Experience with deep
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computer science, mathematics or an equivalent with above-average performance You have very good knowledge in one of the following areas: Programming skills in Python, C++ or CUDA Deep learning frameworks
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computer science or related computational engineering disciplines. Experience with simulation frameworks for complex computer systems and architectures. Some knowledge of accelerator (CUDA, SYCL, HIP) and scientific
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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