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uncertainty. In parallel, the activity of specific neuronal subtypes will be measured. These findings will inform a novel theoretical framework which will be iteratively refined by experiments to selectively
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mathematics, and knowledge in deep learning. Practical experience in a broad range of techniques including LLM training, evaluation, RLVR, PEFT, quantisation, tensor/data parallelism. Ideally, familiarity with
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of error and uncertainty. In parallel, the activity of specific neuronal subtypes will be measured. These findings will inform a novel theoretical framework which will be iteratively refined by experiments
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be the head of the computing unit. About the project The primary research goal will be to create quantitative performance models that describe a range of numerical methods, parallel programming models
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the computing unit. About the project The primary research goal will be to create quantitative performance models that describe a range of numerical methods, parallel programming models, and hardware platforms
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ticketing system, the candidate is expected to provide advanced support in computational science and engineering, big data analysis, machine learning, or any related field. Senior candidate should initiate
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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. Interest in high-performance computing and parallel algorithms. Fully funded 4-year PhD position at KU Leuven and EnergyVille. Research at the forefront of future converter-dominated power systems. Access
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community and the general public in the Denver metropolitan area. The current strengths of the faculty are in the areas of algorithms, artificial intelligence, computer networks, graphics, parallel and