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-order modelling and high-fidelity simulations of turbulent reacting flows. You will have the opportunity of using cutting-edge facilities such as Imperial College HPC facilities. You will have access
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(HPC) systems Background in statistical mechanics, thermodynamics, and molecular modeling The candidate must be independent and fluent in English both oral and written. For further information about the
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
multidisciplinary team. Scientific curiosity, initiative, and motivation to thrive in a translational research environment. Desirable qualification Familiarity with HPC environments and willingness to apply machine
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fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling
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(OMOP CDM, FHIR) or metadata harmonisation Experience with ETL tools, workflow engines, or bigdata frameworks (e.g., Spark, NiFi, KNIME) Familiarity with containerisation (Docker) and HPC or GPU computing
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programming skills (e.g., Fortran, Python; familiarity with Linux/HPC environments). strong motivation to work in an interdisciplinary environment bridging molecular theory, nanoscience, and light–matter
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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-impact weather A dedicated computer scientist/software engineer works alongside you to set up ICON-CLM on the HPC systems, support simulations and manage large data volumes—so you can focus on the science
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learning and signal processing libraries; You have HPC/GPU computing experience, including running deep learning workloads on compute clusters (CUDA-compatible GPUs, multi-GPU training, Slurm). Your master's