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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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Materials and Processes) joint laboratory, a collaboration between the University of Haute-Alsace, the CNRS and Arkema. The PhD student will therefore benefit from an academic and industrial research
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and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and electrotactile
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procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop probabilistic digital twins of coronary arteries. The goal is to create patient-specific
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of the Foundation for Science and Technology (RBI-FCT), by the Research Fellow Statute (EBI), by the Norms for Grant Assignment and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all
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physics, particularly photodetectors or image sensors. Experience in at least one of the following: semiconductor processing, cleanroom fabrication, device modelling or TCAD, electrical characterisation
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discipline. Essential Good programming skills, preferably in Python/C#. Experience with machine learning, deep learning, or experimental AI evaluation. Interest in secure distributed AI, federated learning
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evidence to support the evaluation of AI and machine learning models. This may include investigating data-centric AI strategies, such as data quality assessment, annotation refinement, dataset curation, and
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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opportunities and diversity as a strength and an asset. Description of the workplace The research group for associative learning conducts research in neurophysiology and neuroscience, with a particular focus on