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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 14 days ago
: rigorous, organized, curious, autonomous, proactive and dynamic. A specialization in optimization, machine learning, statistical learning or game theory is appreciated. Research experience is a plus
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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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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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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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Microelectronics teams, the PhD student will be supervised and helped. He/She will access, after training, the IEMN technological platforms. He/She will be provided the tools and computer accesses necessary
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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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parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large
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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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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
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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