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? No Offer Description - work environment: The Institut d’Electronique et des Systèmes (IES) is a joint research unit from U. Montpellier and CNRS. The nanoMIR research group (https
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for the continued development of the European XFEL. The facility's unique strengths, its high-energy linac and long, variable-gap undulator systems, provide a solid foundation for generating intense X-rays at 25 keV
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’ (https://www.uni-kiel.de/en/jma ). With its Early Career Programs, the JMA offers a unique research environment positioned at the interface of the humanities, the natural, and the social sciences
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quantitative backgrounds who are enthusiastic about bringing their expertise to address fundamental problems in biology and medicine using cutting-edge technologies. The Pritykin lab (http
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the aim of understanding the molecular basis of nutrition-dependent diseases, and of developing new strategies for treatment and prevention. The Department of Experimental Diabetology(DIAB) invites
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polypropylenes, contributing to the development of materials for advanced, high-value applications. This will include applying expertise in inorganic polymerisation catalysis and organic functional group chemistry
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and the endoplasmic reticulum. The project will combine approaches in cell biology, biochemistry, and advanced imaging. The candidate will contribute to the development and optimization of experimental
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to improve radar performance - Participate in the selection of electronic systems to be tested - Develop injection methods for the selected systems - Characterize the waveforms used for susceptibility test
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and spatial transcriptomics and epigenomics. More details: https://research.pasteur.fr/en/team/cellular-plasticity-in-age-related-pathologies/ Candidate profiles We are seeking highly motivated
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward