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consistent thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in
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thermodynamic framework; Algorithm development for the numerical resolution of the resulting systems; Numerical simulations and validation of the proposed models. The model will be formulated in terms of gradient
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, immunology, and allergology to better understand the interaction between airway epithelium and mast cells within healthy and diseased airways, identify biomarkers, and develop algorithms for the diagnosis and
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validated algorithms. The objective is to identify sensorimotor signatures of fall risk that may improve current predictive models and contribute to the development of more targeted prevention strategies
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 8 days ago
(Loreley, CEDAR and MAGELLAN). This project aims to design and develop an open-source management solution for a federated and distributed data exchange platform (DXP), operating in an open, scalable, and
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, abandonment, comments, peer interaction) Formalization of algorithms for orchestrating educational AI agents : Train RL and LLM agents and study multi-objective optimization (mastery, well-being stability) Work
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3D environments. • Design of a robust control architecture to ensure autonomous navigation using information from the optical localization system (development of estimation algorithms, use of observers
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
to advancing algorithms for human-centered robots: robots that are not working autonomously in isolation, but that instead react, interact, collaborate, and assist humans. To do so, these robots need
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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Ecole Polytechnique and CNRS, hosted by the Center for Applied Mathematics (CMAP) of Ecole Polytechnique. The Platon project-team focuses on developing innovative methods and algorithms for uncertainty