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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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, or roundabout navigation will be considered. In this work, we also aim to explore the use of machine learning approaches [1][2] to personalize the driving system according to individual driver preferences
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interactions between these different institutions. Research activities related to neuromorphic spike sorting, unsupervised learning algorithms, and neural signal analysis will be primarily conducted in
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://www.crbm.cnrs.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone YahooMail
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member of the French metrology network FIRST-TF, and a member of the REFIMEVE+ project, which physically links our institute to the LTE laboratory in Paris. This thesis will allow the candidate to acquire
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computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
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remains open for the later stages of the PhD. During this PhD, the student will acquire highly valued skills in climate modeling, climate simulation analysis, and will contribute to expand the knowledge
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AntipolisCountryFranceCityVALBONNE Contact City VALBONNE Website http://www.i3s.univ-cotedazur.fr/ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone
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modified under the influence of an external electric field (E). Antiferroelectric materials, on the other hand, have an antipolar dipolar structure corresponding to a net polarization of zero and undergo a
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/InstituteInstitut de Génétique HumaineCountryFranceCityMONTPELLIER Contact City MONTPELLIER Website http://www.igh.cnrs.fr/ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail