43 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" PhD scholarships at Technical University of Munich in Germany
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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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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being excited to make a real impact with
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application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: thesis.mhpc@ed.tum.de More Information https://www.epc.ed.tum.de/mhpc
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interaction-rich scenarios. Ideal applicants will have a strong M.Sc. in machine learning, control, or safety, and hands-on experience with robotics. Apply now: https://lnkd.in/dNjmv835. Deadline: ASAP. We
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on developing the imaging system as well as novel machine learning approaches for image analysis and disease classification using field data from German and Brazilian agricultural trials. Responsibilities Design
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embedded into the quantum technology network formed by WMI, the Excellence Cluster MCQST (www.mcqst.de), the TU München (www.tum.de), Munich Quantum Valley (https://www.munich-quantum-valley.de/), and many
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Requirements: Applicants should hold an MSc or Diploma in Engineering, Computer Science or a related discipline. Background in Machine Learning and Artificial Intelligence. Strong programming skills (Python
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spectroscopy to tackle challenges in photophysics and photochemistry as well as in material sciences. (https://www.ch.nat.tum.de/dynspec/startseite/). We work with (time-resolved) fluorescence, excitation and