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of processing routes for advanced ceramics and surface treatments, with the aim of developing materials and components with tailored properties for demanding applications. SAFRAN is a leading French international
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CNRS 6144), a leading laboratory in process engineering, particularly in electrochemical engineering for environmental applications such as water treatment and reuse, as well as the valorization
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(bbγγ) channels. In the classical HH(bbγγ) analysis, the H(γγ) channel is treated as a major background process for the di-Higgs channel. A joint analysis of both modes would optimize the overall
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controlling the long-term fate of naturally occurring radionuclides within this matrix remain poorly understood. In particular, the processes responsible for the progressive decrease in their mobility over time
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. This thesis aims to model, optimize, and experimentally validate such an optical ultrasound sensor based on resonant metasurfaces. The work will focus on three main areas: 1. Multi-physics Modeling: Development
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perfusion and mechanical stimulation in tumor tissues to investigate their poromechanical properties and optimize molecular transport within explants. The successful candidate will be involved in: - Designing
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capable of automatically selecting the simulation strategy best suited to a given prediction objective, while optimizing the trade-off between accuracy and computational cost. The work will build on multi
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the production and dissemination of a film presenting the project. Supervision Prof. Radouane EL YAGOUBI – Neuroscience, CLLE Laboratory Dr Amel AISSAOUI – Signal Processing, IRIT Laboratory Contact Prof. Radouane
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d'Azur. The team is composed of computer scientists but has a strong interdisciplinary focus, particularly in linguistics, philosophy, sociology, and law. MARIANNE proposes innovative methods for natural
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neuronal circuits requires the coordinated execution of several developmental processes, including neuronal migration, axon growth and guidance, and synaptogenesis. These processes critically depend