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, analytical modelling, and numerical simulations to develop and validate novel reinforcement systems. This position is part of an Innosuisse-funded collaborative project with industry partners, focusing
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between research institutes and industry partners, combining experimental and numerical expertise. This position is part of the ANR DYNATERRE project, which focuses on the static and dynamic behavior
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developments and numerical calculations, especially for objects containing hundreds or thousands of particles. In those cases, it may be convenient to separate the system into several subsystems, some of which
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with data-based models and numerical dynamo simulations. The successful candidate will contribute to studies of time-averaged geomagnetic field morphologies and core dynamics during transitional events
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understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working with data-based models and numerical dynamo simulations
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
, with relevance to submarine glacier melting and other ice-ocean interactions. The position will emphasize both numerical approaches (e.g., Large Eddy Simulation, Direct Numerical Simulation, multi-scale
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- Develop original numerical methods for facility simulation in presence of expansion waves - Demonstrate improved estimates of rate constants for two-temperature models - Contribute
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the Research Group “ Numerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting September 1, 2025. The position is assigned to the research project "Randomization of Surrogates
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soon as possible. The position is within the Math+ project "Anisotropic microfluids -- fluctuations, control, effective models and their numerics “. Here, we study anisotropic microfluids and the effect
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. The project activities will involve the development of the theory and implementation of the advanced mechanics and numerical models as well as constitutive model calibration and validation based on physical