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the subway, S-Bahn or tram Contact: Maximilian Tschochohei, PhD, VIOLET Project, Institute for AI and Informatics in Medicine, Chair of Medical Informatics, Technical University of Munich (TUM
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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
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Qualifications: MSc or PhD in Computer Science, Bioinformatics, Computational Biology, or a related quantitative field. Solid experience in programming and system architecture design (e.g., Python), workflow
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dedicated to improving the understanding of the lunar water cycle, with many applications in the field of solar system science and exploration. To this end, we combine both numerical modelling and
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17.11.2025, Wissenschaftliches Personal The Chair of Computing in Civil and Building Engineering (CCBE) at Technical University Munich invites applications for the position of a Research Assistant
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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of TUM. Kontakt: TUM School of Life Sciences, Functional Materials of Food Pagaging, application.fmp@ls.tum.de More Information PhD PhD in Stimuli-Responsive Elastomers, (Type: application/pdf, Size: 166.9
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/264ffa19ca70e3ec41032fe6a4802932b5eda4e6.pdf https://ieeexplore.ieee.org/document/10068193 Job Specifications For PhD applicants: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically
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junior research group leader with a focus on data and AI Science to join us as soon as possible. Your qualifications PhD in Computer Science, Mathematics, Physics or related fields Experience in applied
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degree or PhD in Computer Science, Electrical Engineering, Control Systems, or a closely related field. Experience in reachability analysis, formal verification/model checking, control theory, or related