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/ coarse- grained approaches) Experience with enhanced sampling techniques; computational biophysics/chemistry Usage of high-performance computing clusters, preferably GPU-based computing Proficiency in
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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13
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humanity. • Access to state-of-the-art facilities, including extensive departmental CPU/GPU computing resources and Imperial’s Research Computing Service. • A vibrant, interdisciplinary research culture
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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Data (CRCD), which operates a large multi-thousand-core cluster with GPU co-processors and PhD-level consulting staff. Pitt ECE also leads the NSF Center for Space, High-performance, and Resilient
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Data (CRCD), which operates a large multi-thousand-core cluster with GPU co-processors and PhD-level consulting staff. Pitt ECE also leads the NSF Center for Space, High-performance, and Resilient
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opportunity to advance your academic career at a world-leading institution dedicated to using science for the benefit of humanity. Access to state-of-the-art facilities, including extensive departmental CPU/GPU
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heat transfer processes Use of advanced numerical methods (CFD, LBM, hybrid models) Utilization of high-performance computing (HPC, GPU) Analysis and validation of numerical results Optimization
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research-focused HPC environment. Project background We train open foundation models with hundreds of billions of parameters on thousands of GPUs on one of the largest AI-ready supercomputers in Europe
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. The Directorate comprises the International Office, led by the Deputy Director International; the Global Partnerships Unit (GPU), led by the Associate Director Transnational Education (TNE); DMU Global; and the