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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 16 hours ago
://www.cmap.polytechnique.fr/~aymeric.dieuleveut/ ), professor at Ecole Polytechnique (Palaiseau). The successful candidate will implement and compare different distributed and stochastic numerical optimization paradigms
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control (MPC) under uncertainty for autonomous systems. The research aims to develop state-of-the-art numerical methods for solving challenging belief-space optimal motion planning problems and their
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prototype different thermal technologies and evaluate as well their integration and control within given hybrid systems, and under different market scenarios and industrial applications. Among
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design theory that facilitates multi-objective, multi-disciplinary optimization of data center design considering location, building operations, materials, energy use, water use, cooling system design, and
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design theory that facilitates multi-objective, multi-disciplinary optimization of data center design considering location, building operations, materials, energy use, water use, cooling system design, and
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or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor minimization and tensor decompositions paired with auxiliary information in order to recover
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. The researcher will also design data-driven numerical approaches to address a variety of real-life optimization models including disaster and emergency logistics, supply chain and transportation. Specific
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) and molten salts - Optimization of synthesis conditions followed by physicochemical characterization of the materials obtained - Synthesis of MXene and hard carbon composites - Preparation of electrodes
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experience in the development of biosensors, preferably applied to the biomedical field, ranging from the design and optimization of sensory platforms to validation in relevant healthcare contexts. 5
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farms. This research will build upon a multi-scale and multi-physics numerical modeling framework, with the goal of enabling rapid and robust probabilistic assessments for design, optimization, and