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AI for Science and Engineering and Foundation Models and Generative AI axes. The recruited candidate will develop contributions at the interface between machine learning, optimization and quantum
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hydrology, hydraulics, environmental sciences or signal processing. A strong expertise in scientific programming (Python, MATLAB) is required. Knowledge of machine learning or deep learning will be a
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Electronique, Energie, Automatique (EEA) ou équivalent. Le candidat doit posséder un bon niveau en mathématique et des connaissances en traitement du signal. Des connaissances en machine learning/deep learning
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analysis and processing: NumPy, Pandas, SciPy; - Machine learning/AI: Scikit-learn, TensorFlow, PyTorch (preferred); - Data visualization: Matplotlib, Seaborn, Plotly. LanguagesFRENCHLevelGood
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, Applications of Deep Learning in Electromagnetics: Teaching Maxwell's equations to machines. Scitech Publishing, 2023. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR6164-DAVGON-024
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the French project BIBLISSIMA+ (https://projet.biblissima.fr ), and the ERC Synergy MIDRASH (https://www.midrash.eu ). The eScriptorium project itself involves North American and European teams and aims
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MICADO (the first light instrument of the Extremely Large Telescope). The project provides a collaborative network, engaging with leading experts in optics, astrophysics, and machine learning from
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recruited candidate will contribute their expertise to the initial training of engineering students and master's students by teaching in the following areas: • Bioinformatics, • Machine learning and pattern
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, thermodynamic aspects of the evolution of materials and interfaces, and resulting microstructures. - Related methods: Design of Experiments and Applied Statistics, with an openness to machine learning methods