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, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with researchers from different disciplines. You have
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. The successful candidate will receive careful mentorship both from the supervisor and from other peers through a dedicated mentorship program. Technical queries should be directed to Benedikt Jahnel
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The Leibniz Graduate School on Aging (LGSA) is a joint program of the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI) and the Friedrich Schiller University (FSU) in Jena. The School calls
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, structured PhD program for all doctoral candidates working at LIV with binding guidelines developed based on the Leibniz Association's guidelines for graduate education. Our program offers multidisciplinary
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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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to uncover new molecular strategies for safeguarding crops. Join a vibrant, interdisciplinary research environment where computational chemistry, biochemistry, molecular biology, and plant science converge
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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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students on the campus, offering the chance to engage and connect - our PhD Representatives offer information and advice when needed access to high-performance computing a chance to contribute meaningfully
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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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. Alexander Ecker (Institute of Computer Sciences, University of Göttingen). Candidate profile We are looking for a highly motivated candidate with: A strong background in animal behavior, behavioral ecology