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Field
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, numerical optimization, numerical partial differential equations, and parallel computing. The Researcher will join a project developing parallel high-order meshing algorithms from medical images and parallel
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, including hybrid simulations coupling machine learning with numerical methods, multiscale discretization, nonlocal closure modeling, structure preservation, multilevel and multifidelity machine learning
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), numerical methods, and basic knowledge of material science. It is meriting to have one or more of the following skills/qualities: experience and/or thorough understanding of theoretical/numerical methods
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lattice field theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging
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applications in real world data sets. We are also interested in exploring opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job
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schemes for their discretization Knowledge of numerical optimization Knowledge of Python, Matlab and FOTRAN90 compiled code, use of high-performance parallel computing servers Ability to synthesize and
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Experience in using parallel computing facilities Desirable: Experience with astroplasma simulations Knowledge of computational methods applied to physics, e.g. Particle-in-Cell. Education: PhD degree in
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algorithms in the context of sparse tensor operations and apply them to real-world datasets. Parallel Computing: Explore opportunities for parallelism in the tensor completion process to enhance computational
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | about 2 months ago
13 Mar 2025 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Recognised Researcher (R2
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magnetism. Qualified applicants must have PhD degree in physics, astronomy, mathematics, engineering, computer science or similar. Experience with numerical methods, preferably within open-source software