46 computer-security "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dip" "Dip" scholarships at Leibniz
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The Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany, invites applications for its three-year PhD program starting October 1, 2026. BIPS, a leading center for
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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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to request one if your application is successful. For further information, please visit the website: https://www.kmk.org/zab/central-office-for-foreign-education.html For further information
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environment. The candidate will be given the opportunity to develop a doctoral thesis with extensive support through the RTG2413 (www.synage.de ) and the CBBS graduate program (gp.cbbs.eu ). Your profile
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an interdisciplinary consortium studying the “GEvol: Genomic Basis of Evolutionary Innovations (GEvol)” (Priority Programme, SPP 2349 funded by German Science Foundation (DFG)). We are recruiting a highly motivated
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
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to gain further qualifications. We offer our employees a broad spectrum of career opportunities in an attractive working professional environment (https://www.dwi.rwthaachen.de/seite/institutskultur). DWI
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector
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to gain further qualifications. We offer our employees a broad spectrum of career opportunities in an attractive working professional environment (https://www.dwi.rwthaachen.de/seite/institutskultur). DWI
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in