186 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" positions at Technical University of Munich in Germany
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Linguistics, Data Science or a similar field Good theoretical knowledge and practical experience with Natural Language Processing (rule-based and/or machine learning) Software Engineering Motivation to build
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skills in statistical analysis, data mining, data integration, machine learning, programming, backend or frontend development, and database design. Additional desirable skills include a sound understanding
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, leveraging a principled combination of passivity-based control methods, machine learning, and human-in-the-loop systems to enable robust teleoperation in uncertain and delayed communication environments. Key
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Bewerbung, abrufbar unter https://portal.mytum.de/kompass/datenschutz/Bewerbung/. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent
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Freising, Germany Tel. +49 8161 71 3961 patrick.bienert@tum.de https://www.mls.ls.tum.de/en/cropphys/home/ www.tum.de The position is suitable for disabled persons. Disabled applicants will be given
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related field. Strong background in robotics, estimation, control, or machine learning. Strong proficiency in Python and/or C++ and experience with ROS/ROS2. Demonstrated research experience (e.g., Master’s
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inspiring international environment and to learn from some of the world's leading researchers · Development of own international industrial and academic network · Independent working
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research and work environment within a young and dedicated team · An exceptional opportunity to experience research in a highly inspiring international environment and to learn from some of the world's
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skills, ability to interact with scientists at different levels good software design skills and the ability to write clean, and reusable code in machine learning, deep learning frameworks, such as
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with