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, environment and ecology, transportation, robotics, energy, culture, and artificial intelligence. Presentation of CNRS as an employer: https://www.cnrs.fr/en/cnrs Presentation of IRISA as the host laboratory
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the SPIN Doctoral School (ed-spin.doctorat-bretagne.fr). This thesis is part of the ANR Ant'noid project (https://anr.fr/Projet-ANR-24-CE33-0218 ). Additional Information Applications must be submitted via
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of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
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, or roundabout navigation will be considered. In this work, we also aim to explore the use of machine learning approaches [1][2] to personalize the driving system according to individual driver preferences
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and validated within the PhLAM team. Consequently, only limited effort will be required to acquire the experimental skills needed for this part of the project, allowing the PhD candidate to focus
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lie at the crossroads of multiple disciplines and involve expertise in optics, electronics, image and data processing (including machine learning), photophysics, chemistry and biology. The position is
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of the century, which could be further amplified by a slowdown in the Atlantic Meridional Overturning Circulation (AMOC). This PhD is part of the French-Brazilian project AMACLIM (https://www.lsce.ipsl.fr/anr
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modern machine-learning techniques, will be exploited to improve the discrimination between the different polarization states. The analysis will use the complete Run 2 and Run 3 datasets collected by
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interactions between these different institutions. Research activities related to neuromorphic spike sorting, unsupervised learning algorithms, and neural signal analysis will be primarily conducted in
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in