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2 Apr 2026 Job Information Organisation/Company École Normale Supérieure Department Physics Research Field Physics » Statistical physics Researcher Profile First Stage Researcher (R1) Positions
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 6 days ago
out research work on problems of statistical estimation with the support of information theory. This research involves a literature review, mathematical analysis, and numerical simulations, as
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candidate will join the “Ecosystem Functioning” research group (ECOFUN - https://ecobio.univ-rennes.fr/ecofun-diversity-interactions-processes ) and will be supervised by Cécile Monard (CNRS Researcher) and
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acquisition). Statistical analysis and computational modelling of cross-linguistic data from a developmental project investigating the emergence of an indefinite article in Hindi. Oral narratives have already
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or expect to complete a PhD in physics or a related field, with strong background in soft matter / nonequilibrium statistical physics / numerical simulation / statistical inference. Scientific skills
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spectrometry techniques available in the laboratory, as well as optimizing analytical methods if necessary; Performing advanced data processing, including statistical and multivariate approaches, and potentially
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models. The project will involve statistical, computational, and theoretical components, including: - derivation of environmental covariates that best reflect resource uptake processes above- and
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. https://research.pasteur.fr/en/job/postdoctoral-positions-in-epidemic-mathematical-statistical-modelling
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of Euclid data. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8262-ELIBLA-002/Default.aspx Requirements Research FieldAstronomyEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research
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obtained in monkeys on implicit statistical learning within our laboratory. • Mastery and adaptation of bio-inspired Hebbian learning models • Evaluation of the ability of these models to account for data