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being responsible for the confocal microscope (maintenance). Resources provided (equipment, IT, etc.): office equipped with a computer workstation, equipped laboratory bench, reagents and equipment shared
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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psychological theory, cultural history, and interdisciplinary research. Good academic writing and communication skills in English. Desirable skills Knowledge of machine learning or advanced NLP techniques (e.g
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that are transforming many sectors today through language models, recommendation systems and advanced technologies. However, modern machine learning models, such as neural networks and ensemble models, remain largely
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and image processing. Prior experience with data fusion, machine learning, or super-resolution methods will be considered an asset. Candidates should be motivated to conduct independent scientific
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teams. Nearly 90 doctoral students, a dozen post-docs, 60 master's or engineering school interns complete the workforce. Attached to the CNRS Institute of Computer Science, its research themes cover a
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of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
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, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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financement Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/133293 Requirements Specific Requirements Etudiant(e) titulaire d'un Master II en Statistique / Machine Learning