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and economy that respect people and their environment. We are looking for our future postdoctoral researcher in model-based reinforcement learning to join the Computer Science and Networks (INFRES
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of transportation and energy. Its experimental and numerical modeling activities focus on various complex and multiphysical flows, including turbulence, two-phase flows, combustion, and thermoacoustics. Research
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applications in vehicular networks (VANET), composed of vehicles and communicating infrastructure elements, for the protection of vulnerable road users (Vulnerable Road Users). Main Activities Contribution
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shown that VRM is associated with changes in the dynamical state of layer (L) 4, but how these changes occur remains unknown. New data suggest that the essential modifications are complex and require
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the advent of the Internet of Things (IoT), any sensor can be interfaced with a local network or the Internet. This massive deployment has created many security issues and associated solutions
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these active modules in complex networks have been proposed [1] and are being studied by the SPARKS team at I3S [2-3]. The mission of the recruited researcher will be to develop a method for identifying active
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cyclization. More specifically, during the thesis, the PhD student will synthesize molecular complexes for grafting onto lithographically patterned gold networks. The entire system will then be used in
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of neuronal networks and how this translates into specific behaviors in healthy and pathological conditions. To achieve these objectives, SPPIN adopts a multidisciplinary approach combining optical microscopy
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network contracts upon local stimuli to orient fluid transport where it is needed. This enables autonomous functionalities without the need for a complex nervous system. These organisms use fluid transfer
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that are transforming many sectors today through language models, recommendation systems and advanced technologies. However, modern machine learning models, such as neural networks and ensemble models, remain largely