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Field
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GPU infrastructure. This Postdoc position is part of the eSSENCE graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from the foundational
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, psychology, economics, political science, social research, engineering, and the humanities; High-performance computing, GPU-enabled workflows, large-scale data processing, research storage, and technical
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for career development Access to high-performance computational resources (with GPUs) A collaborative environment across research fields, including plant biology, quantitative genetics, and population genetics
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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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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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/ 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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, or population genetics Deep learning for sequence, EHR, or imaging data High-performance and GPU computing environments Excellent candidates from adjacent quantitative fields are encouraged to apply. The Research
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the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use similar techniques to make a statistical inference of the population of subhaloes by
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, POPL), verification (e.g. CAV) or top venues in closely related fields. Experience in at least one of the following (ideally more than one): formal verification tools (especially proof assistants), GPU
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(especially proof assistants), GPU programming, low-level systems engineering in languages such as C/C++/Rust, systems for ML. Experience in writing academic papers. Please see job description for a full list