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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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scale and the sample scale. - Establish links between microstructure and mechanical properties, by combining experimental and numerical approaches, with the aim of optimizing material performance. Within
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journals and presentations at conferences. - Collaboration with interdisciplinary research teams as part of the CERTAINTY project. - Optimization and documentation of modeling configurations for future
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heat transfer processes Use of advanced numerical methods (CFD, LBM, hybrid models) Utilization of high-performance computing (HPC, GPU) Analysis and validation of numerical results Optimization
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, …). Some effort may be dedicated to finding a tensor network topology (tensor train, tree tensor network, …) allowing to optimally represent vector fields arising from turbulence simulations. Then, this
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datasets and validating numerical models developed within the laboratory. 2.2 Responsibilities The successful postdoctoral researcher will join a research team developing a unique experimental platform at
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numerical techniques to study collective states in active matter. Depending on the candidate's profile and interests, the research can involve various aspects of the modeling and the optimal control of active
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of mathematical modeling, with a particular focus on stochastic modeling, optimization and more recently machine learning. Indeed, over the last years, the team’s activity has been marked by a strong shift toward