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that serves 15,000 users annually. Co-located with the Molecular Foundry, NERSC supercomputing center, and Berkeley Lab's materials and chemical sciences programs, it provides an ideal collaborative environment
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transcriptomics. Innovative visualization tools and highly automated analytical pipelines powered by GPU technology. Mentorship from experienced scientists in data analysis and management, with an expertise in
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be highly organized, have excellent attention to detail, and possess sound scientific judgment. The position will require effective management of their own time with the ability to plan, coordinate
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excellent attention to detail, and possess sound scientific judgment. The position will require effective management of their own time with the ability to plan, coordinate, and execute multiple tasks
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generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated by our Software Energy Lab, which has multiple test machines with GPUs and AI
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): Programming: HPC (GPU), MPI Fortran / C, C++ Kokkos, Python, Perl Solar physics (numerical modelling with Lare 2d, 3d / MURaM / Bifrost / R2D2) Experience working with large-scale datasets, ensuring efficient
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programme of computer science, mathematics, physics, electrical engineering, computational linguistics, or similar with good grades PyTorch skills: experience in training machine learning models with one
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managing and administering an NVIDIA DGX SuperPod instrument. You and another HPC administrator will partner closely with a team of data scientists from Stanford Data Science to ensure that the GPU cluster
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sitting within a leading programme of clinical, health and bioinformatics at the South London and Maudsley (SLaM) Biomedical Research Centre (BRC) and forms a key component of both the Centre
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-performance computing, including parallel or GPU programming (MPI, OpenMP, CUDA, Kokkos, etc.) Familiarity with modern software development practices, including debugging, profiling, and version control