10 evolution "https:" "https:" "https:" "https:" "https:" "University of St" positions at IMT Atlantique
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-based vision (event cameras), we are recruiting a research and development engineer within our Computer Science (INFO) and Mathematical and Electrical Engineering (MEE) departments. In collaboration with
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-atlantique.fr) and Associate Prof. Christophe LOHR Keywords: Conversational Agent, Debate, Argumentation, Knowledge graph, Generative Neural Networks, Mental health preservation Where to apply Website https
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Vision, Thermal camera, Human movement quality assessment, Functional Capacity Evaluation Where to apply Website https://imtatlantique.fillout.com/mscapf2026 Requirements Research FieldComputer
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Website https://imtatlantique.fillout.com/mscapf2026 Requirements Research FieldComputer science » 3 D modellingEducation LevelPhD or equivalent Skills/Qualifications Background: Robotic control, Robotic
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. Supervisor: Prof. Vincent CASTEL (Google Scholar page ) Keywords: Cavity magnonics; Nitrogen-vacancy (NV) centers; Hybrid quantum systems Where to apply Website https://imtatlantique.fillout.com/mscapf2026
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. Panagiotis Papadakis and Associate Prof. Mihai Andries Keywords: Deep learning, event cameras, human skeleton, pose estimation, action recognition Where to apply Website https://imtatlantique.fillout.com
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, uncertainty propagation Where to apply Website https://imtatlantique.fillout.com/mscapf2026 Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications Skills: Modeling Reactor
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. Where to apply Website https://imtatlantique.fillout.com/mscapf2026 Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Research FieldEnvironmental science » Earth scienceEducation
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Atlantique Bretagne - Pays de la LoireCountryFranceCityNantesPostal Code44307StreetLa Chantrerie, 4 rue Alfred KastlerGeofield Contact City Brest, Nantes, Rennes Website https://www.imt-atlantique.fr/en Street
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unsupervised baseline. • Months 6-18: Development of Generative models for simplex-valued images and integration into inverse problems pipelines. Data preparation for supervised model training. Application