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this goal, it is paramount to characterize the added value of using machine learning in estimating and decoding quantum errors occurring in coded quantum systems. Research program: The PhD student will first
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. Experimental characterization of Hall effect thrusters using combination of diagnostic techniques such as optical emission and absorption, Langmuir probes, etc. enhanced by the application of machine learning
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1 Nov 2025 Job Information Organisation/Company CNRS Department Centre de Recherche sur la Biodiversité et l'Environnement Research Field Biological sciences Environmental science Researcher Profile First Stage Researcher (R1) Country France Application Deadline 21 Nov 2025 - 23:59 (UTC) Type of...
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SICAL team at LIRIS, recognised for its expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. They will
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be done via computer simulations, including Monte Carlo and molecular dynamics, combined with the use of statistical mechanics to predict e.g. phase transitions, nucleation rates, etc. The work will be
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for such applications. To respond to these challenges, this project aims to investigate automated decision making based on machine learning. The candidate (H/F) will propose and validate centralized as
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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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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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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