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condensed matter physics • Ability to learn and develop skills in analytical computation, theoretical modelling and numerical simulations, in particular the numerical solution of partial differential
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, machine learning techniques, etc.) is desirable. This thesis offer within the AstroParticle and Cosmology Laboratory (APC) is part of the Deep Underground Neutrino Experiment (DUNE). DUNE is an
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Contributions - A formal framework for modeling well-being in adaptive learning - A well-being-aware student simulation model - A multi-objective RL framework - An orchestration architecture - Experimental
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the BENEFIT project, funded by the French National Research Agency (ANR), to work on active flow control and machine learning. 1- CONTEXT -------------------- Active flow control aims to modify velocity fields
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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actions, adaptable to the constraints of the work, ability to communicate and to argue a case, powers of analysis, summary and critical evaluation, ability to learn and develop one's skills, flexibility and
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macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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on the interaction between human cognition and language—understood as a cognitive entity, a means of communication, an object of learning and lifelong development, and a sociocultural phenomenon. Mission : Background
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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably