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; - interact closely with the team of Dr. François Robin (Sorbonne University), project partner for the development of experimental results and bioinformatics approaches; - develop statistical tools
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Intelligence, statistical learning, uncertainty management, and knowledge engineering, with applications to knowledge capitalization, recommender systems, and the design of narrative virtual environments. Where
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of pedology and/or hydrology is a plus - Strong skills in ecological data statistical analysis Specific Requirements PhD degree of less than 3 years. LanguagesENGLISHLevelGood LanguagesFRENCHLevelGood
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» Statistical physics Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Country France Application Deadline 2 Oct 2025 - 10:00 (Europe/Paris) Type of Contract Temporary Job Status Full
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criteria - PhD in linguistics, cognitive science or related discipline (equivalent degree to be discussed) - Experience with EMA or other articulatory data acquisition systems (collection and analysis
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
from statistics, optimization and control, in order to build more efficient algorithms able to better estimate uncertainty, exploit structures, or adapt to some non-stationary context. He was the PI
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. Requirements: We are looking for a highly motivated candidate with a PhD in theoretical/computational physics or applied mathematics. A strong background in quantum mechanics and numerical simulations is
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colour centre spins. Your work supporting and further develops the fabrication of these chips, i.e. together with 1-2 PhD students, you will work on the sample process line involving several cleaning steps
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mechanisms engaged when deciding to transmit information in social networks. Candidates must have (or nearing completion of) a PhD degree in neuroscience, social psychology, behavioral economics, computational
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; manage timing, triggers, and metadata; curate datasets to BIDS/MEG-BIDS. * Modeling & statistics: implement laminar source modeling; derive beta-burst features (timing, rate, waveform); link neural