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and genome dynamics: an integrated study in S. pombe The objective of this research project is to explore the mechanisms of cellular adaptation to environmental changes in the yeast Schizosaccharomyces
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: The MOVING project aims to develop an ethnographic and interdisciplinary methodology for studying the traces and memories carried and transmitted through bodies, of African slavery in post-slavery and
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for the heliophysics component, and LISN in Orsay for the computer science and natural language processing component. Status meetings every two weeks, alternately at LIRA in Meudon and at LISN in Orsay. The PhD thesis
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
insurance (subject to conditions) Gross Salary per month: 2300 € Selection process Website for additional job details https://jobs.inria.fr/public/classic/en/offres/2026-10248 Work Location(s) Number
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Ifremer's INCOGNITO project. This site allows for the study of deformation-fluid coupling at various scales, from the continental to the offshore domain, and provides key constraints on the permeability
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 months ago
Framework Programme? Not funded by a EU programme Reference Number 2026-10252 Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD thesis will take place in
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Préhistoriques (HNHP, UMR 7194) laboratory is a joint research unit under the supervision of the CNRS, the MNHN, and the UPVD. Its mission is to study the biological and behavioral evolution of hominins over
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. Anomaly Detection and Fault Diagnosis using Frugal AI • Selection, feature extraction, and construction of relevant indicators from electrical signals and supervisory data. • Study of signal processing
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the desired accuracy at minimal cost. • Study the interactions between different modeling levels (RANS, RANS/LES hybrid approaches, LES). • Develop multi-fidelity methodologies that enable the effective