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Internship Job title Internship in AI: Graph-based Artificial Neural Networks H/F - Grenoble Subject The internship is focus on evaluation of Graph Neural Network coupled with radar sensor data. The fisrt
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the understanding of reliability physics, and optimizing their potential down to deep cryogenic temperature. [1] https://irtnanoelec.fr/programme/q-loop-preparer-le-controle-commande-de-lordinateur
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) en master (M1 ou M2) ou en avant-dernière ou dernière année d'école d'ingénieur, en data science, mathématiques appliquées, génie nucléaire ou physique. Solides compétences en data science Bonne
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premier ordre pour mener à bien vos missions. pour plus d'infos : https://fames-pilot-line.eu/dc-dc-conversion-inside-advanced-packages/ Description du poste : Participe au CEA-Leti au
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to millikelvin and can reach large magnetic fields. Our expertise lies in electric, thermoelectric, and thermal experiments for studying quantum materials in extreme conditions. https
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representation methods for the analysis of experimental data from multiple diagnostics of the WEST tokamak, with a particular focus on multivariate time series and their time-frequency representations
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and per task, and preservation of the communication. It was extended to partitioned multicore deployments and to the coherence of the data each function reads. These properties are necessary but not
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, crafted through cutting-edge additive manufacturing. With your passion for in situ 3D imaging of physical phenomena and your expertise in material science, physics and experimental methods, you'll
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. Moyens / Méthodes / Logiciels Python, Matlab, SPECTRA Profil du candidat Vous préparez un Bac+5 (Diplôme École d'Ingénieurs, master 2 ou équivalents) en computer vision, data science, IA, traitement du
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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