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The INM research group Structure Formation is seeking for a motivated Doctoral Researcher interested in the self-assembly of nanoplatelets (NPLs) for optical applications. This PhD project is part
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Experimental Sciences or equivalent training programs; - PhD Degree in Chemistry; - Training in DFT and CASSCF computational methods and molecular dynamics studies; - Experience in physicochemical and structural
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Life Sciences, sub-area of Structural Biology, with emphasis on Structure based drug development, within the scope of the project CryoEM@NOVA, funded by European funding (European Comission), under
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to these structures to cross the bacterial envelope and ensure the injection of its genome into the host. This ANR-funded project aims to unravel the molecular events and dynamics of the infection process of
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aspects. Experience with quantitative research methods and data analysis. A good understanding of the political and administrative landscape and the complex dynamics within and around the greenhouse
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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of proof assistant technology capable of understanding the dynamical linguistic structures found in current high-level mathematical texts. The project includes the study of interpretation mechanisms
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within a Research Infrastructure? No Offer Description ABOUT THE ROLE Joining a dynamic, multi-disciplinary team, you will support the project Investigators to drive forward research activities
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(mechanical, electromagnetic, and, possibly, fluid-dynamic) and multi-scale simulations for drone components using finite element tools (e.g., Abaqus, Comsol). · Supporting the development of an AI