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Field
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to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering structure preserving Finite Element methods for multiphase flows
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The post-doctoral researcher will contribute
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Summary/ Department Summary: The GPU is a procedural unit running 5 days a week for both ambulatory and inpatients. The GPU performs a wide range of non-sterile procedures: examples include; therapeutic
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candidate, skilled in numerical model development (programming in FORTRAN, numerical methods, HPC environment). Experience in numerical methods on unstructured grids and/or GPU would be strong assets
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transformative AI projects. MINIMUM QUALFICIATIONS Expert knowledge of at least one major cloud platform (AWS, GCP, or Azure) Strong programming skills in Python and infrastructure-as-code tools Proficient with
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programming proficiency in Python and C/C++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA
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application workflows across CPU/GPU clusters, parallel storage, and hybrid cloud platforms. Responsibilities include configuring and optimizing large-scale Linux environments, implementing job scheduling and
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2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number MIS DHNet Is the Job related to staff position within a Research Infrastructure? No Offer
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of education and experience totaling four [4] full-time years may be considered. (Student experience may be considered.) Two (2) years of full-time directly related programming or systems
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engineering applications through the exact same governing equations. The software for this work is our state of the art open source multiphysics weakly compressible SPH solver DualSPHysics [3] with GPU hardware