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computational approaches Beyond technical training, you will join a dynamic, collaborative and international team and receive structured support through our PhD training program. Your Profile: Master’s degree
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with process based erosion models, field measurements and atmospheric boundary layer processes detailed knowledge of GIS, Google Earth Engine, and programming in these systems high degree of initiative
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. This highly collaborative project, jointly investigated by PDI, TU Munich, University of Münster and HTW-Berlin, is funded by DFG within the priority programme SPP2477 "Nitrides4Future". The motivation is to
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or similar, obtained by the start date Experience in modeling using Python, MATLAB or similar Basic programming skills Proficiency in scientific English (written and spoken) Willingness to spend several months
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the knowledge graph Your profile Masters, Diploma or equivalent degree in Bioinformatics or similar, obtained by the start date Experience in programming and databases Basic biological understanding Proficiency
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the programme area ‘Plant Adaptation’ (ADAPT). The aim of the research project is to understand how intrinsically disordered regions (IDRs) and prion-like domains (PLDs) control the temperature responsiveness
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QCLs) for high-resolution spectroscopy. Within the framework of the priority program INtegrated TERahErtz sySTems Enabling Novel Functionality (INTEREST) funded by the German Research Foundation (DFG
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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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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
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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