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Field
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extracting transport properties from molecular dynamics trajectories. ● Experience with GPU-accelerated machine learning frameworks (for example CUDA, PyTorch, or GPU-enabled LAMMPS). ● Experience
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towards a sustainable future. Subject description This project focuses on the development of GPU-accelerated, high-fidelity thermal runaway simulation models for lithium-ion battery cells, modules, packs
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collaborators and strong access to compute through national GPU systems (NAISS, e.g. Berzelius and Arrhenius) and local GPU infrastructure. Project description The position offers significant scientific freedom
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Interactions external link groups, with close interaction with bioinformatics, microbial ecology and experimental crop research at the UU and NOAH partners. You will have access to Utrecht University GPU/HPC
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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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-to-end GPU timing; document limitations and extrapolation behavior. Implement, test, document, and maintain open-source Python/JAX research software; collaborate with researchers to connect trained models
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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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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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, SimpleITK, MONAI, or nibabel), knowledge of Linux, Git, virtual environments and containers (Docker), and experience in training models on GPU in secure environments are required. Languages: Oral and written
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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