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Field
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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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Engineering, or a related field Strong experience in building and optimizing AI systems using PyTorch, TensorFlow, or JAX Practical knowledge of NVIDIA GPU programming (CUDA) and experience with inference
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partner for Boston College faculty, research departments, and programs in advancing the Boston College research mission, and will work with the director develop long-term plans to support faculty research
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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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administration. Experience with one or more of the following technologies: Automation User/Group Management Storage Systems GPU programming and GPU support Networking Preferred Qualifications: High Performance
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health, vision and dental insurance, child care and student loan subsidies, generous levels of time off, 403(b) Retirement Savings plan, Pension, Tuition and certain License and Certification Reimbursement
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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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in chemistry, physics, or related field. At least 2 years of experience developing quantum Monte Carlo algorithms. Strong problem-solving and analytical skills. Python programming experience. GPU
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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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): 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