102 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" positions in France
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technologies, such as low-power long-range (LoRa) and high-throughput, low-latency technologies (5G). In the context of machine learning, communications play a central role in data sharing and in the decision
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 5 days ago
joint project between the laboratory “Reproduction et Développement des Plants” at Ecole Normale Supérieure at Lyon (https://www.ens-lyon.fr/RDP/ ), Mosaic team at Inria Lyon (https://team.inria.fr/mosaic
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et d'assurer la stabilité des performances dans le temps. Cette thèse s'inscrit dans le cadre de l'apprentissage continu, un domaine émergent du machine learning, qui vise à concevoir des modèles
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 days ago
) Optimization and parameter identification methods Data-driven modeling and machine learning Physics-Informed Learning (or hybrid modeling approaches) Handling and analysis of large-scale datasets (e.g., mobility
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of deep learning in many disciplines, particularly computer vision and image processing. Consequently, coding architectures based on deep learning and end-to-end optimization have been proposed [Ding 2021
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of: • machine learning • cybersecurity • distributed systems • privacy-enhancing technologies The research will be carried out within the (team name) at LS2N, focusing on trustworthy AI and cybersecurity
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Description The doctoral student will study the integration of molecular motors into supramolecular self-assemblies, and how the mechanical work generated by the actuation of the molecular machine will
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8197-VALHER-223/Default.aspx Requirements Research FieldMathematicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research
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for highly motivated candidates currently enrolled in a Master’s degree or engineering program in applied mathematics or computer science. Candidates should have a solid background in machine learning and be
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expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. As part of the project, the PhD student will work with