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of studies, coordination of study implementation, data analysis and interpretation (with a focus on neuroimaging data analysis, usage of AI and/ or computational modeling of psychological processes
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22.03.2021, Wissenschaftliches Personal The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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22.11.2020, Wissenschaftliches Personal The 3D AI Lab at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer vision, machine
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15.06.2020, Wissenschaftliches Personal The 3D Understanding Group at the Technical University of Munich is looking for highly motivated PhD students and PostDocs at the intersection of computer
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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on the Bildungscampus Heilbronn (Heilbronn Education Campus). TUM Campus Heilbronn focuses on the areas of managing digital transformation, family businesses, and computer science. Requirements - Master’s degree in
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, building model checkers (also verified by automated theorem proving) etc. - AUTOMATA TUTOR (available at [1], described in publication [2]) is a tool to teach undergraduate students the basics of theoretical
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
control of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random