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24 Apr 2026 Job Information Organisation/Company CNRS Department Groupe de recherche en Informatique, Image, Automatique et Instrumentation de Caen Research Field Mathematics History » History
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energy consumption. Design, model and evaluate new proposals. Document, publish and present the results obtained. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment
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parallelization strategies Experience with porting and optimization of parallel HPC software for modern architectures including GPUs Excellent knowledge of a variety of suitable computing languages (including C
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différents types de parallélisme, que ce soit au niveau d'un nœud de calcul (CPU et GPU) qu'au niveau d'une grappe de PC. Cet environnement inclura les outils nécessaires à la description et à la construction
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international journals or conferences. Experience in predictive modeling for forecasting or recommendation systems. Strong programming skills in Python and AI frameworks (PyTorch, TensorFlow), including GPU/cloud
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://www.uu.se/en/department/immunology-genetics-and-pathology Read more about our benefits and what it is like to work at Uppsala University Colorectal cancer (CRC) is the third most frequently diagnosed cancer
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/ frederic.giroire@cnrs.fr Laboratory: COATI team, I3S laboratory (Université Côte d’Azur/CNRS) and Inria (https://team.inria.fr/coati/ , https://www.i3s.unice.fr/en/) Place: Centre Inria de l’Université Côte d’Azur
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direction is the generalization to parallel GPU computations. Task 4: Correctness evaluation of quantum communication systems and quantum protocols. This task will include approaches such as statistical model
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frameworks (PyTorch, TensorFlow). Experience with dataset curation, annotation workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data
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Information Benefits Trabajo en IA generativa de vanguardia aplicada al habla / Work on cutting-edge generative AI for speech Acceso a servidores GPU y recursos de cómputo / Access to GPU servers and computing