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, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management
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parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria We are looking for a colleague with a PhD in particle physics. Experience with machine learning and/or experience with
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that are transforming many sectors today through language models, recommendation systems and advanced technologies. However, modern machine learning models, such as neural networks and ensemble models, remain largely
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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
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
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. • Strong knowledge of signal processing methods and machine learning. • Familiarity with regulatory and ethical constraints in research involving sensitive data. • Ability to work closely with
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of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
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perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
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Research Infrastructure? No Offer Description The PhD will take place at LAMIH-UMR CNRS 8201, Université Polytechnique Hauts-de-France, Valenciennes, France. It is part of the JCJC ANR TeCAPE project