208 proof-checking-postdoc-computer-science-logic positions at Technical University of Munich
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://mediatum.ub.tum.de/doc/1696192/aab7jokzk7x4paq7m2y9pa2p6.Wetzlinger-2022-NAHS.pdf Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related
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28.07.2025, Wissenschaftliches Personal The Chair Group of Production and Resource Economics at the TUM School of Management and the TUM School of Life Sciences offers a position as Ph.D. Student
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/d) in Energy Informatics. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research
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tools? This research area sits at the intersection of Human-Computer Interaction (HCI), Artificial Intelligence (AI), and Software Engineering (SE). The goal is to design and evaluate new interaction
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27.05.2025, Wissenschaftliches Personal At the Technical University of Munich (TUM), we offer a Science Coordinator position (m/f/d) to shape, coordinate and manage the newly established Climate
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14.07.2025, Wissenschaftliches Personal This opportunity is offered by the Chair for Philosophy and History of Science and Technology at the TUM School of Social Sciences and Technology (SOT). ABOUT
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/d) in Energy Informatics. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research
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of Logistics and Supply Chain Management, has been selected as a Henriette Herz Scout by the Alexander von Humboldt Foundation. He can recruit up to three postdocs or early career researchers from abroad with
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17.03.2025, Wissenschaftliches Personal We are searching for 5 Ph.D. students, and 2 Postdocs in Mechanical/NanoMaterials Engineering for an EU project, TV-L E13, full-time Phase change and
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq