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of their respective concentrations will be investigated and correlated with the velocity field recorded by PIV (Particle Image Velocimetry). In parallel with the use of standard post-processing methods, an innovative
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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working on related topics Participate in teaching and supervision activities, in line with the candidate's profile and interests The research activities will be hosted by the Parallel Computing and
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et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få en oversikt over besøkene
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disease prognosis. This position offers a unique opportunity to work at the forefront of optical imaging technology, combining experimental optics with advanced computational and data-driven methods. Roles
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modern high performance computation facilities and parallel computing clusters (CPU and GPU). Excellent publication record and demonstrated conference presentation skills. Demonstrated ability to operate
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modern high performance computation facilities and parallel computing clusters (CPU and GPU). Excellent publication record and demonstrated conference presentation skills. Demonstrated ability to operate
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Researcher (R2) Application Deadline 26 Mar 2026 - 22:59 (UTC) Country Sweden 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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substantial knowledge and research experience in areas such as computational fluid dynamics, turbulence modeling, data-driven methodologies, machine learning, and parallel computing. The candidate should also