396 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" PhD positions in Germany
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” at the same time that you apply for admission to the Master's programme (https://www.my-stuwe.de/en/housing/halls-of-residence-tuebingen/ and https://www.my-stuwe.de/en/housing/faqs/ ) and send in a copy of
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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required, as we offer German courses as part of the programme. Application deadline Please visit https://www.uni-muenster.de/Baccara/application/index.html . Submit application to https://www.uni-muenster.de
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problems Proficiency in data analysis and programming using at least one statistical program such as R, Python, or similar programming languages Experience with GAMS, GTAP, and Exiobase is an asset. Skills
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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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dynamics Chemistry » Homogeneous catalysis Chemistry » Computational chemistry Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 13 Mar 2026 - 23:59 (Europe/Berlin
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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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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD position in Translational Cell Biology (f/m
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Degree PhD Doctor of Philosophy Course location München Teaching language English Languages English only Full-time / part-time full-time Programme duration 6 semesters Beginning Winter and summer
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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