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Field
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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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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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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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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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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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DeepMD, NEXMD, i-PI, MixPI, NWChem, CP2K, or comparable packages. Experience with GPU acceleration, distributed training, high-performance computing systems, or C/C++ scientific software development
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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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Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred. Familiarity with GPU-accelerated genomics, high-performance computing, or cloud-based analysis
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(UTC) Country Italy Type of Contract Other Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a