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Field
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turbulent flow simulations. 3. Background in numerical methods and scientific computing. 4. Proficiency in Python programming and high-performance computing on modern GPU-based platforms
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potentials or force fields (for example MACE, NequIP, DeePMD). ● Experience running scientific calculations on Linux-based high-performance computing clusters, including scripting or workflow automation
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runaway models and numerical methods in OpenFOAM. Design and optimize computational frameworks for high-performance simulation of reacting flows and battery safety phenomena on modern GPU architectures
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computational modelling of additive manufacturing and develop high-performance GPU-based CFD solvers. Qualifications • With PhD degree • Strong research experience in developing GPU-based
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compensation and working conditions. Basic Qualifications Ph.D. or M.D./Ph.D. in areas such as machine learning, computer science or closely related field. Excellent programming skills and practical experience
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/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics and/or magnetohydrodynamics Radiative transfer in
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with machine
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trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. Depending on the day, we
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Postdoc Position in AI Foundation Models for Crop Microbiomes Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
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. Understanding of local hardware optimization (GPU/VRAM management). Comfortable putting together a simple working interface for a workflow (e.g. Gradio) — no formal UX/UI design background required. Able