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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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                Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 1 month 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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                Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 2 months agoOffer Description Funding: 36 months, CIFRE (https://www.anrt.asso.fr/fr/le-dispositif-cifre-7844 ) Starting date: November / December 2025 Keywords: Physically informed machine learning, Industrial 
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                The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning 
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                the Linux file system - Extending BPF capabilities if required - Designing and implementing benchmarks to evaluate the prototype - Writing a scientific paper to present the results Where to apply E-mail job 
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                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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                (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone YahooMail 
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                - work environment: Research Laboratory. - main mission: The goal is to design and prototype a Reciprocating Expansion Machine with a Linear Alternator (REMLA – 200W–100Hz – 10mm stroke), coupled with 
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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