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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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, machine learning (PINN, supervised learning) - Python/PyTorch programming - Autonomy, curiosity, and adaptability - Excellent writing skills Specific Requirements The doctoral student's host laboratory is
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 3 months 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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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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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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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
authorities. École des Ponts ParisTech, in accordance with its strategic plan, develops a long-term research activity in the field of Machine Learning and Computer Vision. The IMAGINE team is a renowned
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18 Nov 2025 Job Information Organisation/Company Université Savoie Mont Blanc Department LLSETI Research Field History Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country
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sciences » Biology Biological sciences » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 1 Dec 2025 - 10:00 (Europe/Paris) Type of Contract
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network capable of both inference and learning, aiming at investigating candidate architectures for ASIC design in a longer-term future beyond the scope of this PhD work. Thesis objectives As part of