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Field
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, and simulations, machine learning, high-performance computing, CANFAR, or advanced data systems. Evidence of mentoring or supervising undergraduate students, graduate students, junior researchers, or
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competencies at LLNL. Fellows participate in experimental, computational, and/or theoretical work, and will have access to LLNL's extensive computing facilities, talent pool, specialized laboratory facilities
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on R&D and innovation, the changing nature of working tasks, and business performance. Professor Fulvio Castellacci and Associate Professor Markus Bugge coordinate the TIK Centre’s work in SURE-AI
Searches related to high performance computing
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