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Programme? Not funded by a EU programme Reference Number PEPR-DIADEM Is the Job related to staff position within a Research Infrastructure? No Offer Description The present PhD proposal is part of the project
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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-SofT project, the recruited person will: - design novel algorithm for large-scale block-sparse tensor computations that are suited for massively parallel accelerated supercomputers. - investigate the use
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measurements, and simulation results Integrate data engineering workflows with HPC-based simulation environments Optimize and parallelize software solutions for execution on one of the world’s most powerful and
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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(Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 38h30 Offer Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by
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to enable quantitative, high-resolution, time-lapse monitoring of soil properties and will be implemented using high-performance parallel computing. This PhD position offers the opportunity to work at the
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Application Deadline 31 May 2026 - 23:59 (Europe/Bratislava) Country Slovakia Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Science, Computer Engineering, or a related field, completed before the fellowship start date. Candidates should demonstrate experience in at least two of the following areas: compilers, parallel programming
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environments. Experience with parallel computing environments, HPC in a Linux environment. Experience with surrogate modeling. Experience with data analytics techniques. Familiarity with C++ and GPU programming