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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 20 hours ago
Website https://jobs.inria.fr/public/classic/en/offres/2025-09541 Requirements Skills/Qualifications Eligible candidates should have a PhD in computer science. Experience in formal methods or in
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of the creation of a specific program on Digital Humanities and Artificial Intelligence (DHAI) within ELLIS, with the aim of strengthening the unit's engagement in this interdisciplinary area. These
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Minimum education and/or experience required: PhD obtained less than 3 years before date of hire in Computer Science, in one of the following areas: Data Science, Artificial Intelligence, or related field
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engineeringYears of Research Experience1 - 4 Additional Information Eligibility criteria - PhD in bio-informatics, biophysics, biochemistry, biology, physics, chemistry, mathematics, informatics or related
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FieldComputer scienceYears of Research ExperienceNone Research FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria The candidate must hold a PhD in computer science (or a
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LevelPhD or equivalent Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in ecological, marine or computer science with skills in python and/or R, QGIS, database and
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based on a computational approach and artificial intelligence, in collaboration with Brest University Hospital and Multiwave (Marseille), we are recruiting a doctoral student or postdoctoral researcher
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This experimental (non-linear photoluminescence
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23 Oct 2025 Job Information Organisation/Company Télécom Paris Research Field Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions Country
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scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in computer science Background in probability, Markov chains, MDPs Knowledge about reinforcement learning and planning are a plus but not necessary