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feeds Scaling analog in-memory computing towards large generative AI models H/F 192 / 778 vacancy Vacancy details Position description Category Micro and nano technologies Contract Internship Job title
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; PyTorch; parallel and GPU computing Applicant Profile The internship is intended for a final-year Master’s student or engineering student specialising in applied mathematics, signal processing or
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Computing Devices at CEA-Leti in Grenoble, you will contribute to the development of Bayesian learning methods suited to resistive memories (ReRAM). You will build on the team’s previous work, which
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emerging applications requires low–temperature operation of CMOS transistors, such as spatial applications, high performance computing, high energy physics…, with a temperature of operation below 100K
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réduire les performances de lecture et de manipulation des qubits. Intégré à un laboratoire de recherche en conception intégrée, et en particulier au sein de l’équipe quantum computing, vous aurez
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library for computing the elementary matrices associated with near, singular and quasi-singular interactions using advanced integration methods from the literature [2–6], or variants to be defined as
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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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équipe et bonne humeur ; Vous avez une première expérience dans une infrastructure IT distribuée et complexe de type HPC ou cloud computing (formation en alternance, expérience professionnelle) ; Vous
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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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-manual dexterous setup to reliably solve complex assembly tasks. The following works conducted at the lab will serve as a basis for the internship: https://cea-list.github.io/cotograspweb/ https://cea