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, or optimization**, connected to **artificial intelligence** and the research of **Antonin Chambolle** and his collaborators at CEREMADE. The position is a research position. The candidate will interact mainly with
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capable of automatically selecting the simulation strategy best suited to a given prediction objective, while optimizing the trade-off between accuracy and computational cost. The work will build on multi
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Processes (https://simap.grenoble-inp.fr ) - is a multidisciplinary laboratory with more than 200 participants from chemistry, physics, materials and fluid mechanics. It is one of the leading laboratories in
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perfusion and mechanical stimulation in tumor tissues to investigate their poromechanical properties and optimize molecular transport within explants. The successful candidate will be involved in: - Designing
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the transfer of heat, fluids, and gases from the mantle to the crust, crustal deformation and the evolution of sedimentary basins through flexural isostasy in response. However, these large-scale processes
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the simulation of turbulent flows using a tensor network representation of the Navier–Stokes equations. Unlike recent approaches based on tensor networks, which simulate fluid flows in physical space using finite
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systems still face major challenges when operating in fluid environments such as air or water. Unlike ground robots, aerial and underwater robots exhibit dynamics that are strongly coupled with
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hypothesis is that seismicity serves as an observable proxy for the coupled processes linking deformation, permeability evolution, fluid circulation, and hydrogen generation. The strategy consists
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particular, the postdoctoral fellow will work on three complementary areas: - Development and optimization of imaging analysis protocols Improvement of hyperspectral and multispectral photoluminescence (HMSPL
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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