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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 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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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
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Memory and Computing Devices (LDMC) at CEA-Leti develops emerging memory technologies and explores their use for data storage and computing. Its research combines device design, fabrication and
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. To achieve this, it draws upon its scientific expertise across a wide range of high-tech fields, including artificial intelligence, software design, simulation, cybersecurity, and quantum computing
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a reliability-aware design platform for FDSOI technology in those extreme environments. Contract duration (months) 6 Job description As an intern at CEA, you will have the opportunity to work in a
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Description de l'offre Nous rejoindre, pour quoi faire ? Au sein de notre laboratoire possédant une expertise en design, fabrication et caractérisation de µLED, nous proposons un sujet d’optimisation de
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l'offre Stage - Problème inverse et simulation de métasurfaces par deep learning génératif Sujet de stage Simulation en utilisant des modèles de substitution (Surrogate Networks) et design inverse de
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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