337 evolution "https:" "https:" "https:" "https:" "Queen's University Belfast" Postdoctoral research jobs in France
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numerical results with observations from scanning and transmission electron microscopy provided by the partners of the ANR project IMP3D (https://anr.fr/Projet-ANR-24-CE08-3737 . - Select a discrete
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confirmation. About LAPTh (https://www.lapth.cnrs.fr ): LAPTh is a joint research unit (UMR) of CNRS and Université Savoie Mont Blanc (USMB). Its scientific activities span cosmology and astroparticle physics
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; Identification of functional, technical, performance, economic criteria, goals and indicators for classifying/comparing UPB methods. Development of a comparison multicriteria method. For the solutions emerging
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, materials science, and advanced nanofabrication. This project focuses on the development of functional optical metasurfaces with engineered responses tailored for selective optical camouflage. The targeted
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at interfaces and in the bulk. The work will involve operando electrical and optical characterizations, spatially resolved analyses of performance and degradation mechanisms, and the development or adaptation
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), combining state-of-the-art in vivo approaches with quantitative data analysis. About the lab and environment The Rebola Lab (https://therebolalab.org ) studies how variability in synaptic function across
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conflicts threaten children’s education across the world. Because such disruptive events tend to obstruct data collection, understanding their impact on children’s educational development is challenging
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atmospheric plasma to treat fibrotic diseases. The agent will join the emerging Innovative Cancer Treatment team. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8175-LAUFOU-002/Default.aspx
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Montpellier Website https://www.inserm.fr Street 208 Av. des Apothicaires, 34090 Montpellier Postal Code 34090 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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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