47 machine-learning "https:" "https:" "https:" "https:" positions at Technical University of Munich
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ENGAGE Network at TUM and GIM Robotics. About the ENGAGE Network Mobile working machines (MWM) are critical to industries like construction, mining, and agriculture, and key to Europe’s sustainability and
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, sta-tistics, machine learning
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academic assignments at the chair What we look for in you Completed master’s degree in computer science, transportation, or related engineering fields Solid background in generative AI, machine learning, and
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Researchers: Ph.D. in Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent
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robust, user-friendly frameworks for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics. The research combines continuum mechanics, machine
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robust, user-friendly frameworks for multimodal elastography and enabling deployment on portable devices (e.g., smartphones) for real-time diagnostics. The research combines continuum mechanics, machine
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for safety-critical bilateral teleoperation. The research will leverage a combination of passivity-based control methods and machine learning techniques to enable reliable and robust teleoperation in uncertain