49 computer-vision-and-machine-learning PhD positions at Technical University of Munich
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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, C++, etc.) Knowledge of machine learning, data mining, or related fields Excellent communication skills and ability to work in a collaborative team environment Interest in social science research
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master’s degree in Computer Science, Geodesy, or related discipline Very good programming knowledge, preferably in Python Experience with state-of-the-art machine learning or data science technologies
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environment using machine learning technologies. This PhD position is part of our research on exploiting social media data for earth observation tasks. The work will be on the topic of developing geographically
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evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric modelling is greatly beneficial. Excellent English and the willingness to learn the German language
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group, a multinational insurance company. Tasks Your duties will include: Literature research Designing, implementing, and evaluating novel machine learning approaches to detect building attributes from
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for this position, the candidate should possess in-depth skills in programming and hands-on training and evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric
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Science, Computational 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
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. The main focus is developing and characterizing metallic high-performance materials for/through additive technologies using experiments and computer-aided methods. Furthermore, the chair is dedicated
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research and travel budget available to best support your research. You will partic-ipate in teaching and supervising students, interact with and learn from the other team members, and re-ceive close