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. Development and integration of state-of-the-art machine learning techniques in the analysis and event reconstruction will be a major component of this work. - Characterization of silicon detection modules using
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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generative artificial intelligence, machine learning, and ontologies to automatically align heterogeneous competency frameworks. The research will focus on: Formal modelling of competencies and educational
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Profile This multidisciplinary thesis requires strong expertise in several of the following areas: Robotics, computer vision, control systems, dynamic modeling, signal processing, or machine learning
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interactive robotics, with solid expertise in control theory, robotic perception, or machine learning for robotics, or more broadly AI for autonomous systems (computer vision, multimodal AI, speech and language
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supplemented by seismological data—using machine learning methods (statistical or deep learning). As part of this thesis, we will use a dataset of approximately 1,000 numerically simulated earthquakes (already
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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Specific Requirements Required Profile: Master degree in computer science or applied mathematics, Engineering school. Background and experience in machine learning. Good technical skills in programming
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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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are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset