76 postdoc-in-system-identification PhD positions at Technical University of Munich in Germany
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27.10.2025, Wissenschaftliches Personal Are you passionate about generative AI and digital twins for intelligent mobility systems? Do you see potential in using large language models, vision
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, University of Galway), Africa and the Americas. The Chair of Livestock Systems is newly established at TUM includes one postdoc, two PhD students, visiting researchers and technical staff. The team involves a
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05.04.2023, Wissenschaftliches Personal We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated
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(m/f/d) in the topic: “AI-based processing of CAD models for automated planning of computer-aided manufacturing.” The candidate has the opportunity to pursue a doctoral degree (Ph.D.). Remuneration is
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to pursue a doctoral degree (Ph.D.). Remuneration is 100% TVL E13 according to the German public sector rates. CCBE's interdisciplinary team is performing research in the broad field of computational methods
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10.11.2025, Wissenschaftliches Personal The Leibniz Institute for Food Systems Biology at the Technical University of Munich (LeibnizLSB@TUM) is a prominent member of the Leibniz Association
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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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systems involved in an effective health care system, rather than creating new medical treatments. Our recent studies have been motivated by two parallel questions: How can we encourage people to engage with
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synthetic chemistry, self-assembly, and functional materials. Prior experience in organic and/or polymer synthesis is highly desirable. Familiarity with supramolecular chemistry, scattering methods
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interoperable methodological framework for AI in gynecological oncology. Your tasks: You will contribute to the development of explainable AI systems and the core methodological framework: Contribute