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at the University of Ljubljana. The HEXAPIC project aims to develop a novel high-performance Particle-In-Cell code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By
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collaborative culture of the group. One position is funded by the Simons Collaboration on Learning the Universe (LtU). The Simons Collaboration develops physically grounded models for galaxy formation simulations
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4 Sep 2025 Job Information Organisation/Company CNRS Department Microbiologie Moléculaire et Biochimie Structurale Research Field Chemistry » Physical chemistry Chemistry » Computational chemistry
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6 Sep 2025 Job Information Organisation/Company CNRS Department PHysicochimie des Electrolytes et Nanosystèmes InterfaciauX Research Field Chemistry » Physical chemistry Chemistry » Computational
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will work on the simulation of an iodine Hall
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Performs basic or applied research in the area of computational fluid dynamics and computational aeroacoustics, including problem setup, simulation and advanced post-processing for multiple projects
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scienceYears of Research ExperienceNone Additional Information Eligibility criteria * Background in marine geosciences, computational geodynamic modeling, physical volcanology and/or seismology. * Familiarity
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are expected. Skills : - knowledge of plasma physics, or nuclear physics - use of Monte Carlo simulation codes (GEANT4, MCNP, FLUKA, or other) to simulate the sounding of materials by neutrons and X-rays
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 days ago
high-order (HHO) methods [2], for which the curl-curl problem (magnetostatics) has been studied recently [1, 3]. The post-doc is essentially concerned, in the context of ECT simulation, with the physical
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simulations and multiscale spatial-omics data. • Integrate uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments