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through various channels. The ifo will actively support you in this. What we expect from your profile a degree with excellent grades, preferably in economics or mathematics, physics or a related field
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accounting of third-party funded projects (in particular by the EU), proficient use of IT tools (MS-Office, especially Excel, SAP), excellent English language skills, good mathematical understanding, high
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the project can be emailed to Dr. Bernd Heinold, heinold(at)tropos.de . We seek a bright scientific mind holding a master's degree in meteorology, physics, mathematics or a related environmental science field
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, computer science, applied mathematics, computational biology, bioinformatics, and many other subjects relevant to the project. Excellent communication skills in English, verbally as well as in scientific
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The mission of the Leibniz Centre for Agricultural Landscape Research (ZALF) as a nationally and internationally active research institute is to deliver solutions for an ecologically, economically and socially sustainable agriculture – together with society. ZALF is a member of the Leibniz...
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in a relevant subject area (e.g., Atmospheric Science, Climate Modelling, Mathematics, Physics, or related field), numerical modelling experience, and a good scientific publication record appropriate
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With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and resilient horticulture. The IGZ conducts research at the interface between plants, humans and the environment. In...
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must have a university degree (master/diploma) and a PhD in meteorology, oceanography or a related natural or geoscientific discipline with pronounced physical-mathematical components. The ability
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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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PhD candidate. We are looking for a person with a background in (bio-) statistics, mathematics or related disciplines who is interested in longitudinal data analysis, causal inference and applications