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feeds Stage - Modélisation géométrique de métasurfaces pour la simulation et le design-inverse H/F 183 / 713 vacancy Détail de l'offre Description du poste Domaine Optique et optronique Contrat Stage
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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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? To achieve these objectives, the intern will be expected to: - Review the state of the art on gaussian splatting reconstruction and 3D perception - Design, develop and evaluate a novel deep learning
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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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to a scientific publication. Context : The main objective of the internship is to investigate, design and implement an abductive explanations and concept-based decision procedure. What do we expect
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models (e.g., [3]) to accurately localize and track objects of interest. • Robust Grasp Control: Design and implement a dedicated hand controller capable of executing dynamic and reliable grasps based on
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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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/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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: 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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will be to study the electrical properties of these building blocks and consider the design of power transistors and diodes that could use them. Another aspect will involve a literature review of the