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activities: - This research is based on a detailed analysis of atmospheric measurements from a multi-sensor network (remote sensing and surface stations) using statistical analysis and a physical understanding
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 6 days ago
Python and good analytical skills. A good background in probability/statistics and deep learning is expected. Knowledge of differential privacy and/or fairness is a plus, but not necessary. The candidate
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(Probability, Statistics and Modeling Laboratory, CNRS-Université de Lorraine), EDF (Electricité de France), and Fives-Prosim. This doctoral program focuses on generative models for energy cycles. Its main
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knowledge of the use of command line and programming (bash and R), -Strong skills in statistical analysis, -Good ability to work in a team, -Good command of English (reading, writing, speaking), -Good
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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industrial process control remains under-explored; the current approach relies on statistical tests or conventional machine learning. One of the manufacturing processes addressed in this thesis is injection
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skills : We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and
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. Experience in statistics is also desirable. In line with CEA's commitment to the integration of disabled people, this job is open to all. The CEA offers accommodation and/or organisational possibilities
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for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any
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the organising principles of biological information processing, focusing on the underlying physics of computations and sensory environments. This exploration has led to developing models and advanced statistical