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actions in distributed power grid systems at INSA Lyon (France). This thesis is co-supervized by LAAS-CNRS. Future energy networks will increasingly rely on interconnected and distributed infrastructures
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, which establishes the theoretical foundations for integrated distributed computing over future wireless networks through: • multi-user computation models; • communication-computation co-design; • function
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chemodiversity, which can be used to analyse the distribution and evolution of families of metabolites of interest. Activities ➢ Description of the research activities : Select and collect plant specimens from
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with deep-learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum, the deadliest malaria parasite species (read [1] to learn more about the ideas behind
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and distributed sensing applications over optical fibers. The work will involve advanced manipulation of the phase of ultra-stable lasers, the development and implementation of advanced modulation and
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France: analysing the influence of French Guyana, the Antilles and Brazil on regional distribution networks. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8239-ELERUS-003/Default.aspx
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to address the deployment limitations of multi-purpose robots in shared environments. Rather than a single monolithic controller, the robot is treated as a network of collaborating semi-autonomous agents (a
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 months ago
an experience in computer networks. Theoretical expertise: distributed systems, P2P networks Good collaborative and networking skills, excellent written and oral communication in English Good programming skills
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(7913), 319-324. https://doi.org/10.1038/s41586-022-04672-7 Hourcade, C., Juhel, K., and Bletery, Q. (2025). PEGSGraph: a Graph Neural Network for fast earthquake characterization based on Prompt
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structure and hydrogen migration pathways. Integrated Approach and Modeling Framework The project is based on a multiscale observation strategy that combines dense nodal seismic networks, distributed acoustic