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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
expose the successful candidate to cutting-edge genome editor engineering approaches and the delivery of these reagents in vivo via AAV or lipid nanoparticles. The successful candidate will also learn
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Functions Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets Modeling plant growth, carbon allocation, stress response (e.g
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administrations, including eBus Competence Center, Emile Weber, GomSpace, Gradel, IEE, Nexxtlab, Telindus, and Ville de Luxembourg. For more information on the ATLAS IPBG Programme, see here: https://edu.lu/wwpy7
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Senior Researcher in Ecosystem based marine management, nature restoration, and anthropogenic imp...
-index and ORCID (see http://orcid.org/ ) Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here . Applications received after the deadline will not be considered. All interested
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-intensive physics with nuclear/particle aspects, advanced detector R&D, machine learning and AI and emerging computational methods in quantum computing. The position is intended for an excellent and broadly
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): Chemical modification of graphene derivatives. • Stage 2 (1 months): Characterization of chemically modified graphene derivatives. Where to apply Website https://sede.udc.gal/services/electronic_board
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team selection announcements” section: https://daip.uvt.ro/anunturi-selectie-echipe-proiecte/ Email, in compliance with GDPR Period for submitting appeals regarding file evaluation Date: 20.02.2026
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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apply through the Careers at UF website at http://jobs.ufl.edu . Required documents include: An application letter summarizing research interests and goals Curriculum Vitae that includes a complete list
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in