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a Master's program (M2) or an Engineering School (including gap year students). • Practical experience in robotics, specifically with ROS2 knowledge. • Strong skills in computer vision and machine
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arrays. Applicant Profile You are a final-year Master’s or engineering student specializing in electrical engineering, microelectronics, applied physics or computer science. You are comfortable with
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Scaling analog in-memory computing towards large generative AI models H/F Subject Your work will span device-to-algorithm co-design, focusing on state-of-the-art small language model engineering and
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Profil du candidat Currently enrolled in your final year of a Master's program (M2) or an Engineering School (including gap year students). Strong skills in computer vision and machine learning
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: Master's (M2) or engineering-school student in machine learning, applied mathematics or computer science Strong linear algebra; probability and optimization are a plus Solid Python and PyTorch Care in
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!), used in future quantum computer or spatial radio astronomy applications This internship provides an opportunity to improve our understanding of reliability physics at cryogenic temperature, and to offer
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qualifications master student or equivalent (2nd/3rd engineering school year) in computer science and/or machine learning; some knowledge of the Python programming language; ability to work in a team
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Congress of Embedded Real Time Systems (ERTS 2026) , 2026. ⟨10.82331/ERTS.2026.42⟩. ⟨hal-05513843⟩ [2] Eclipse Aidge. https://eclipse.dev/aidge/ [3] Projet DeepGreen - https://deepgreen.ai/ [4] Projet
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/Computer Vision pour analyser les images radioscopiques d'un mélange triphasique. Stage M2 de traitement et d'analyse d'images issues de radioscopies X de mélanges triphasiques. Mise en œuvre de méthodes de
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sustainable future. Position location Site Grenoble Job location France, Auvergne-Rhône-Alpes Location Grenoble Candidate criteria Recommended training Last year of engineering and/or equivalent masters