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scripting language is necessary for prototyping. Interest and affinity for high-performance computing are necessary for the position. You should have experience with the roofline model and familiarity with a
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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
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-)Statistics, (Bio-)Informatics, Computer Science or related disciplines Strong background in modeling multi-modal data (images, tables, text, etc) Understanding of biases and causal inference Experience with
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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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22.04.2022, Wissenschaftliches Personal The Professorship for Environmental Sensing and Modeling at the Faculty of Electrical Engineering and Information Technology is researching topics
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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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, climate and earth system modeling, soil parameter mapping, and multi-sensor segmentation, together with our partners at renowned international and national institutes such as Bonn University, Alfred Wegener
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• Integrated sensing and communication: fundamental limits and algorithm design (1 PhD, Mari Kobayashi, mari.kobayashi@tum.de) • Optical fiber channel modeling, receiver processing, and coding (1PhD, Gerhard
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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