430 structures "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at CNRS
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on simulating nanoalloy structures to create a database for materials characterization. The main tasks include running molecular dynamics and Monte Carlo simulations to model nanoalloys under various
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. Using all-atom molecular dynamics simulations and enhanced sampling techniques, the project will investigate how S-glutathionylation modulates nucleosome structure and dynamics, alone and in combination
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quantify the evolution of the thermal structure of the Aquitaine Basin's crust and mantle using the geological record. Geophysical data, the subsidence history of sedimentary basins, and thermal-mechanical
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the network, as well as with academic and non-academic partners. General information about the CLIMES project is available at: [https://www.climes.se/climesdn/ ](https://www.climes.se/climesdn/ ) All working
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), Ryoji Shinya (Meiji University, Japan). Background: Mignerot et al. 2024 https://doi.org/10.7554/eLife.88253.2 Kanzaki et al. 2021 https://doi.org/10.1038/s41598-021-95863-1 Our team (http://ibv.unice.fr
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motivated to acquire new skills. Candidates must be fluent in English and/or French with scientific writing skills. The doctoral contract will take place at the CRISMAT laboratory (https://crismat.cnrs.fr
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for homogeneous photocatalysis. Physico-chemical characterization Structural, optical, and electronic analysis of materials (spectroscopies, microscopies, electrochemistry, etc.) to establish structure–property
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impact measurements, AFM imaging, and AFM-SECM experiments. The SEEAFM project will be developed within the Electrochemistry group of the IMF team at the CEISAM laboratory. Where to apply Website https
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photophysics under conditions simulating those of the interstellar medium. Structural characterization, electronic absorption, electronic fluorescence, and recurrent fluorescence are studied through in situ
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collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at