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conditions and validate the developed models. Candidate Profile: We are looking for a candidate with a background in numerical simulation, who is also interested in learning experimental electrochemistry
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funded by the TIRIS program “Interdisciplinarity and impact of science for society” of the University of Toulouse. As part of this contract, the aim will be to acquire multi-isotope data on gold materials
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—such as reinforcement learning and meta-learning—he/she will develop advanced feedback loops that allow dynamic, real-time adjustments of agent models and interrogation strategies. This proactive approach
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; the candidate should therefore have a team spirit and an interest in conducting research with colleagues from other backgrounds. The candidate will acquire expertise in conducting research projects centered
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the opportunity to acquire knowledge and multidisciplinary know‐how in inorganic chemistry, materials science, physico-chemistry of hydrates, and photophysical characterizations. In addition, the candidate will
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the student to acquire different complementary knowledges Selected references: a) J. Crassous, et al. J. Am. Chem. Soc. 2022, 144, 7709; b) S. Rigaut, et al. J. Am. Chem. Soc., 2019. 141, 20026; c) J. Crassous
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organized in four poles: “Computer Mathematics”, “Data Analytics and Machine Learning”, “Efficient and Secure Communications”, “Modeling, Simulation and Learning” and “Proofs and Algorithms”. The Ph.D
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and mathematical physics. In addition to their research work, doctoral students will take courses offered by the IP Paris doctoral school. They will also have the opportunity to teach if they so wish