47 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Technical University of Munich in Germany
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, transforming the EU into a modern, resource-efficient, and competitive economy. Responsibilities and qualifications The focus of this PhD/Postdoc project is to develop a new Li-operated potentiometric
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, or machine learning is also appreciated. PhD: The candidate is expected to have some background in theoretical computer science, including some of the following areas: automata, logic, games, verification
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
learning • robotics and/or mechatronics • computer languages C, C++ and Python and interest to work in an interdisciplinary environment are desired. German language skills are necessary for this position
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26.02.2025, Wissenschaftliches Personal We are looking for a postdoctoral researcher (f/m/d) with a PhD in Simulation Technology, Computer Science, Mechanical Engineering, or a related field. About
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-quantum cryptography and coded computing (1 postdoc, 1 PhD, Antonia Wachter-Zeh, antonia.wachter-zeh@tum.de) • Theory for communication systems beyond Shannon's approach (1 postdoc, 1 PhD, Christian Deppe
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support throughout your time at our Center. We look for… • a team player with completed (or nearly completed) doctoral degree (PhD or equivalent) in management, organizational psychology, sociology
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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of empirical research (quantitative or experimental) methods, • knowledge of statistics, programming languages (e.g., Python), natural language processing, machine learning is advantageous but not