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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
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-robot-teams
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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 network coding
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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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experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets for livestock systems in East Africa, and in the subtropics in
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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 Kramer