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. Fluorescence lifetime is a powerful probe of molecular interactions, chemical environment and local medium properties, both in living cells and in nanostructures or functional materials. The project therefore
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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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, the energy efficiency of buildings is a major challenge. Building envelopes, designed to protect occupants from external climatic variations, play a key role. Over the past 50 years, numerous models have been
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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collaborators. The activities will include: • Electromagnetic modeling and numerical simulations (e.g., FDTD, FEM) • Design of metasurface architectures based on dielectric materials available at CRHEA
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Postdoctoral researcher (M/F), synthesis of crystal phase heterostructures by Molecular Beam Epitaxy
optical characterization equipment. Close collaboration within a multidisciplinary research team (material growth, in situ electron microscopy, modeling, optics). Regular interactions with project
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ultrafast imaging, compatible with the observation of living biological systems, while remaining applicable to the study of nanostructures and functional materials. The recruited researcher will contribute
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conductivity) of the different constituents is essential to supply material data to the digital models used to design industrial parts, and to understand their behavior under mechanical, environmental, and
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electrogravimetric response. To do this, we will implement a multi-stage approach, combining the development of model electroactive materials, their physico-chemical characterisation, and the advanced exploitation
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; astronomy and astrophysics; high-energy physics; biology and health sciences; fusion energy production and management; material sciences; aeronautics, automotive. The NumPEx Exa-SofT project aims to develop