64 programming-"the"-"DAAD"-"EURAXESS"-"Prof"-"U"-"UCL"-"U.S"-"Empa" positions at Leibniz
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement. This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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, and research-based public and educational work. Over the next ten years, the Museum für Naturkunde will realise its plan for the future. New laboratories and jobs for cutting-edge research will be
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%, limited for 3 years, start: as soon as possible) in the trilateral program “Future Proofing Plants to a Changing Climate” (funded by DFG, UKRI-BBSRC, NSF, USDA-NIFA) Who we are: The research group Symbiosis
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of standard MS programs and a good command of written and spoken English. What we offer Employment in accordance with the collective agreement for the public service of the federal states (TV-L) A modern, well
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, Marine Geology and Marine Observation works interdisciplinary within a joint research programme. What will be your tasks? This position will be embedded in the overarching programme “STB - Shallow Water
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computer scientist with programming experience, but no background in science communication - or vice versa - we still encourage you to apply. Your tasks and duties will be a subset of the following
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, Marine Geoscience, Physical Oceanography and Marine Observation) cooperate within the framework of a joint research program. Project and job description Within KOFI, the long-term carbon storage of marine
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to qualification programs and further training opportunities Remuneration according to the collective agreement of the federal states (TV-L) up to E 13 (including annual special payment) Company ticket A collegial
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in machine learning, AI and programming skills, e.g. Python basic knowledge of materials science / materials engineering Leibniz-IWT is a certified family-friendly research institute and actively
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the