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Field
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, learning as well as task and movement planning. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UPR8001-GUISAR-001/Candidater.aspx Requirements Research FieldComputer scienceEducation LevelPhD
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of you Required PhD in machine learning, physics, or a related field. Established expertise in deep learning (familiarity with graph neural networks, transformers, diffusion and flow based generative
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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Science, Statistical Physics, or any other related field. The skills that we are looking for include: Statistical analysis & causal inference Data management, collection & visualization Social network analysis & graph
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dynamical systems on graph with modern power grid systems as an application. Education and Experience: Applicants must have recently completed a Ph.D. and have exceptional research potential. Teaching may be
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include statistical analysis, data management and collection, causal inference, network analysis, graph theory, visualizations, and online tool development. Experience in conducting online controlled
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relevant expertise: A PhD in Computer Science or a closely related field, with specialization in Quantum computing and Graph theory In this role, you will be responsible for conducting research on graph
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for one year in the Post-doc program in Marseille. Full job description: https://sync.lis-lab.fr/index.php/s/N9wZXjMNH7QcEf5 TYPE OF CONTRACT: TEMPORARY JOB STATUS: FULL TIME APPLICATION DEADLINE: 31/10
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Associate’s, Post-doctoral fellows, etc. in the preparation of manuscripts and presentation materials by creating slides, charts, graphs and handouts. Maintains up-to-date files and records of research data
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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab , the 6GSPACE Lab , the HybridNetLab