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to develop new methodologies based on Low-Field Nuclear Magnetic Resonance (LF-NMR) for the multi-scale characterization of the hydric and thermal properties of natural porous materials used in sustainable
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to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UPR3212-YARSYC-005/Default.aspx Requirements Research FieldNeurosciencesEducation LevelPhD or equivalent Research FieldPsychological sciencesEducation
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The overall objective is to develop a predictive model and aging laws
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ammonia decomposition. Within this project, we are seeking for a PhD candidate to develop In Situ and Operando characterization for the different catalysts that will be tested and modelled by the other
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for identifying the precursor signals of rare events and/or bifurcations in turbulent flows. The role of the post doc will be to develop the necessary techniques using the available tools. A comparison
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of the inverse problem as a function of the target accuracy level, identify the most relevant characteristics of the surface signals, and develop machine learning methods to reconstruct the slip (or its main
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a warming climate. The aim of this PhD project is to develop a numerical tool that can predict glacier collapse by constraining unknown material parameters through the reanalysis of several observed