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reactors, combining the advanced multiphase fluid dynamics, cavitating flow control, and reactor engineering. The successful candidate will: Design and optimize hydrodynamic cavitation reactor geometries
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or continuum mechanics of fluids or solids? The Max Planck Institute for the Physics of Complex Systems (MPI‑PKS) in Dresden announces the opening of several postdoctoral positions in the area of Biological
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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skills, both verbal and written, are required. Key duties: Successful candidate is expected to: Setup, validation, and evaluation of Computational Fluid Dynamic (CFD) models for the elucidation
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UMR 6524, Clermont-Auvergne University. Collaboration with the IMFT (Institute of Fluid Mechanics, Toulouse) for the numerical modelling. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6524
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skills : Interdisciplinary collaboration (fluid dynamics + acoustics + scientific computing) Analytical thinking Scientific curiosity Resilience (handling failed simulations/experiments) Initiative
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for further advancing large-scale 3D-LPT techniques in aerodynamic testing environments. The position centres on experimental fluid mechanics and on the further development of measurement approaches for three
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 19 days ago
for PDEs, with a particular emphasis on turbulence modeling and turbulence control. Your tasks Developing machine learning methods for nonlinear PDEs arising in fluid dynamics and related systems
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differential equations (PDEs). While all applicants with a background in the analysis of PDEs will be considered, candidates with prior experience in theoretical physics, fluid mechanics, kinetic theory
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-UNICAMP) in São Paulo state, Brazil, is to develop methodologies based on Artificial Intelligence (AI) to enhance Fluid Antenna Systems (FAS) and to fundamentally address the scalability challenges of 6G