48 machine-learning "https:" "https:" "https:" "https:" "https:" positions at Technical University of Munich
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Optimization (DPO) and reinforcement learning from human feedback, building preference datasets together with clinicians - Build and run a Red Team process with physicians, computer scientists, and patient
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reproducible research practices. Your responsibilities Develop and implement computer vision and image processing algorithms for star tracking and satellite detec-tion using event cameras. Design and build a
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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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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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, statistics, machine learning) - a high motivation and the ability to work independently with a strong team orientation - excellent spoken and written English and the will to acquire a certain working language
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-good university degree in economics - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) - a high motivation and the
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data Your Profile The ideal applicant has a strong background in bioinformatics and/or probabilistic machine learning, as well as experience in omics data analysis, and possesses solid English-language
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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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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management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance