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at IP2I (LMA) and extreme adaptive optics (XAO) for exoplanet imaging at CRAL. This interdisciplinary initiative aims to develop a new generation of wavefront sensors capable of achieving sub-nanometric
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for geophysical flow modelling, uncertainty quantification, and high-performance computing. Its work relies on both deterministic and statistical approaches. The objective of this PhD project is to develop a new
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. Depending on the candidate's profile and interests, the thesis may develop along one or several of the following directions, at the crossroads of statistical physics, biophysics, and machine learning
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postdoctoral researchers. The proposed thesis topic is part of the ANR NeOClick project, which aims to develop OrganoClick reactions involving organocatalysed cycloadditions that use fluorescence as a probe
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Timenanolive and the ANR project in collaboration with Insitut Langevin, to montior live cells at the nanoscale.During the PhD, the aim will be to develop a new implementation enabling the localisation
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This recruitment will take place within the framework of the PEPR moleculArXiv, the objective of which is to prepare macromolecules containing digital information. The recruited person will join the Laboratory
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of the microstructure, possibility of one step synthesis / shaping of the SSE membrane while ensuring scalability and low cost. The produced materials will be characterized by XRD and SEM/TEM, and used to prepare Solid
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), such as domain walls, vortices, and skyrmions. In this proposal, we aim to extend it to three-dimensional topological spin textures (3DTST) beyond 2D skyrmions. To achieve this goal, we will: (i) develop
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well as their social and cultural determinants, with applications in key areas such as education, health and industry. At the interface between experimental psychology (social, cognitive and developmental) and
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the ARS Mayotte teams to present their findings and develop their research project. Additionally, they will have the opportunity to engage with national networks in mathematical epidemiology modeling