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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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to real-world error patterns by means of learning methods. This requires a recognition of the diverse and complex error patterns that can occur in quantum devices in real-world scenarios. To achieve
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network capable of both inference and learning, aiming at investigating candidate architectures for ASIC design in a longer-term future beyond the scope of this PhD work. Thesis objectives As part of
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 2 months ago
: rigorous, organized, curious, autonomous, proactive and dynamic. A specialization in optimization, machine learning, statistical learning or game theory is appreciated. Research experience is a plus
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. Experimental characterization of Hall effect thrusters using combination of diagnostic techniques such as optical emission and absorption, Langmuir probes, etc. enhanced by the application of machine learning
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SICAL team at LIRIS, recognised for its expertise in HCI and education, including adaptive gamification, engagement, learning analysis, and the design of motivational affordances in education. They will
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Offer Description Funding: 36 months, CIFRE (https://www.anrt.asso.fr/fr/le-dispositif-cifre-7844 ) Starting date: November / December 2025 Keywords: Physically informed machine learning, Industrial
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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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biomedical research. Your profile Master's degree in computer science or related discipline Experience with Python and recent deep learning frameworks (e.g. Pytorch, MONAI) Strong interest in image analysis
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models, multi-view computer vision, semantic graph-based representations, and self-supervised learning—to automatically interpret and understand complex surgical procedures. The overarching goal is to