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Collaborative Research Centre TRR 181 "Energy Transfers in Atmosphere and Ocean" | Kiel, Schleswig Holstein | Germany | 9 days ago
for Meteorology, Helmholtz-Zentrum Hereon Geesthacht, Leibniz Institute for Baltic Sea Research Warnemünde, Leibniz Institute for Atmospheric Physics Kühlungsborn, Goethe University Frankfurt, Hamburg University
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molecular simulations, machine learning, statistical physics, multiscale modeling, and uncertainty quantification. The position is offered in the context of the EU funded project, aiming to develop a novel
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and integration process in Germany Scientific Resources State-of-the-art infrastructure and Core Facilities Work-Life-Balance Flexible working hours and flexi-time models Family Support On-site
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://www.dissgea.unipd.it/selezione-2024as04-il-conferimento-di-un-assegno-di-tipo-24-mesi-selection-announcement-2024as04 Selection process Please see https://www.dissgea.unipd.it/selezione-2024as04-il-conferimento-di-un
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activities, enriching your academic and professional skills. Application Process: Interested candidates should submit the following documents (preferably in a single PDF) to Prof. Dr. Enkelejda Kasneci
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collaborating groups. Selection process Candidates are invited to send their application ASAP, preferably by e-mail, directly to [email protected] Please send a single .pdf file including a
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to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art.13 of the General Data Protection
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cumulative PhD thesis and supervising MA students Requirements: PhD or Master’s Degree in Physics, Engineering, Economics, Environmental Sciences, Mathematics, Computational Sciences or a related field
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pollution, an existential threat to Europe and the world, impacts the safety, comfort and health of humans and vegetation. It is the largest environmental cause of multiple mental and physical diseases and of
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application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and