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information about the network: https://euraxess.ec.europa.eu/jobs/401249 1. Context and Challenges Title: Physics-Informed Neural Operators (PINO) for Ultra-Fast Tomography: Toward Fundamental and Generalizable
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, Apptainer/Singularity) for HPC and cloud portability Querying, transforming, and summarizing major genomics resources (GTEx, GEO) Version-controlled project delivery in Git-based repositories for transparent
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to communicate complex ideas in an understandable way to a broad variety of stakeholders. Demonstrated programming skills in Python and familiarity with areas in AI/ML, such as Natural Language Processing, HPC
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to Stockholm–Arlanda International Airport. More information about the department/division: https://www.slu.se/institutioner/vaxtbiologi-skogsgenetik/ Read more about our benefits and what it is like to work
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for online and off-line tasks, for robotic applications and possibly for LLM reasoning applications in the future. The work will involve designing algorithms, running experiments on the HPC, analyzing
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Linux OS and related programming tools and environments. Experience with maintaining code repositories and code and data versioning (e.g., Git). Experience with HPC (e.g., Singularity, Docker, Slurm
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computing (HPC) systems, including GPUs, and programming, such as using CUDA, MPI, AI/ML/DL, and advanced debuggers and performance analyzers. Familiarity with working on open-source projects. About UF
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modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent
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skills Experience working in Linux/HPC environments Ability to conduct independent research and publish in peer-reviewed journals Strong written and verbal communication skills in English *for students
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broad exposure to CHPC’s technical environment, including HPC systems, research workflows, software development, and AI‑related initiatives. Collaborate with or observe other managers and teams as