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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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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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which currently consists of 5 permanent researchers, 2 PhD students, 2 postdoctoral researchers. The PhD studies will be performed in the experimental rooms of the propulsion team at LPP in Palaiseau
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD student will work in the
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be included in the Combustion axis, and as a PhD student (M/F), you will be registered in the SMEMAG doctoral school (ED 579 - Mechanical & Energy Sciences, Materials & Geosciences). The EM2C
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simulations, optimisation, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https
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promote understanding of the interrelationships between human health and the environment, while strengthening the power to act individually and collectively. The main mission of the post-PHD researcher is
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") team of the laboratory. Supervisory Team: The project is supervised by Malgorzata Chmiel (Géoazur, CNRS) and Jean-Paul Ampuero (Géoazur, IRD). The PhD student will work in close collaboration with Margot
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) familiar, over-learned areas. The research program consists of four work packages. The recruited PhD candidate will be responsible for Work Packages 1, 3, and 4: - WP1: In-depth understanding of visually
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researchers in the efficient and clean use of renewable synthetic fuels. Candidates will acquire advanced skills in combustion science, chemical kinetics, and numerical modeling. Each PhD will lead to a double