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. The second part of the mission concerns a research project focused on polymer foams (60% of the time). This project aims to understand how the distribution of solid material between cell walls and struts can
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), this one-year postdoc position aims to develop a catalytic reaction to convert biobased furanic derivatives to building blocks with applications in the field of polymers and solvents. Building on previous
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properties are optimized by machine learning algorithms to retrieve properties of reference flames gathered in a learning base. A virtual scheme consists of a main block that models the heat release from
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candidate will join the SIGNAL team under the supervision of Dr. Yoan Coudert. Research topic : The recruited postdoc will investigate the genetic mechanisms underlying the pre-patterning and development at a
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and homeostasis, as it regulates the distribution of cell fate determinants in asymmetric divisions. In the model system Drosophila neural stem cells (NSCs), it has been established that cortical
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spatial and seasonal distributions of PFAS and identification of the key processes controlling their fate (dispersion, transformation, sediment retention). Contribution to modeling PFAS transport in
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enables high activity in olefin polymerization, while providing precise control over composition and molecular weight distribution. However, this activator remains a poorly defined solid at the structural
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UVP (Underwater Vision Profiler) database including Particle size distribution (PSD) and concentrations from ship-based rosette deployments, BGC-Argo profiles, gliders, moorings, and other platforms
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Hospital, where in vivo acquisitions are performed. Work will be distributed between both sites depending on project needs. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7587-PEDBAR-004
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advanced seismic methods (including array processing, machine learning, and potentially distributed acoustic sensing) to develop novel approaches for monitoring unsteady and non-uniform flood flows across