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external research funding through national and international funding agencies Active involvement in assessment and evaluation program of IFW What we offer: The research group will be supported by dedicated
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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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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interests, successful applicants will have the following qualifications: Completed or soon-to-be-completed doctorate in one of the following or related disciplines: information science, science studies
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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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knowledge in the application and development of NGS wet lab or computational methods for the analysis of genome data for molecular biodiversity research, have strong experience in data management and analysis
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., KonsortSWD, NFDI), including working groups and collaborative initiatives. Your profile Completed PhD (or near completion) in a relevant field such as economics, statistics, data science, informatics, or
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data analysis using R or Python good skills in scientific writing practical experience with modelling on compute clusters is an asset We expect: the ability to work independently and on your own
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, 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 sediments and the
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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