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utilise molecular backbones that have been little studied to date, based on weak interactions between electron-rich and electron-poor moieties in a chiral environment. The PhD student recruited will be
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applicants to contact us by email in advance. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UPR8011-WOLBAC-001/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD candidate will be integrated into the Unité de Catalyse et Chimie du
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offers and actions on https://cluster-ia-enact.ai/ . You will work in a rare environment at the intersection of frugal AI, analog computing, reconfigurable electronics and THz imaging. The PhD is directly
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Université de Lorraine. Focused on materials and processes science and engineering, it covers: materials, metallurgy, plasmas, surfaces, nanomaterials and electronics. By 2025, IJL has 259 permanent staff (34
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, Microelectronics and Nanotechnology (UMR CNRS 8520 – https://www.iemn.fr/en/ ) is located in Villeneuve d'Ascq, near Lille, France. With a total staff of over 500, the institute has a broad research scope ranging
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Infrastructure? No Offer Description This project is part of the European Commission Marie Sklodowska-Curie (MSCA) Doctoral Network GRAIL “Gamma Radiation from the Atmosphere for Investigation and Learning” https
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at the Institute of Electronics, Microelectronics and Nanotechnology (IEMN), located in Villeneuve d'Ascq, in the Hauts-de-France region. IEMN is a research institute founded by the French National Centre
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safer-by-design and higher performance microbatteries (µBs) is also much-awaited to satisfy the increasing demand for miniaturized embarked electronics, e.g. to power Internet of Thing (IoT) objects with
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the environmental impact of cloud infrastructures, making this PhD topic highly relevant to national and global sustainability goals. Scientific Objectives This thesis aims to develop novel methods for deploying AI