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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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compression and its co-optimization with memory technology characteristics and constraints. You will work within CEA-Leti and CEA-List institutes, benefiting from a forefront ecosystem for AI model
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Optimization of Core-Shell Microcapsules Formation in a Centrifugal Microfluidic Device for the Standardized Production of Organoids Contract duration (months) 6 months Job description As part of an innovative
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publication about this benchmark. # Cea List Moyens / Méthodes / Logiciels AI, Deep Neural Network, Computer Vision, Human behavior analysis Profil du candidat Profile - Students in their 4th or 5th year
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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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gaussian representation meets perception models for bev segmentation. In : 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. p. 2250-2259. [3] KERBL, Bernhard, KOPANAS
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workspace learning,” in European Conference on Computer Vision, 2026. [3] A. Brazi, B. Meden, F. M. de Chamisso, S. Bourgeois, and V. Lepetit, “Corr2distrib: Making ambiguous correspondences an ally to
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characterization process. • 3D Image Processing & Analysis: Actively contributing to 3D image reconstruction, segmentation, and quantitative analysis. • Method Optimization & Automation: Developing
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materials optimization. You will interact with CEA-Leti teams working on FeRAM fabrication and advanced characterization. Applicant Profile You have a background in materials science, physics or
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promising industrial sectors. In this context, artificial intelligence (AI) algorithms have undoubtedly demonstrated their effectiveness for tasks related to vision, with various sensors (camera