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. Particular attention is given to optimization under uncertainty, the optimization of systems with dynamically incoming information, and the optimization of data collection. Through this research, we contribute
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the newly established research team for the ERC Advanced Grant project “Equilibrium Learning, Uncertainty, and Dynamics. (Please find a German version below the English text.) The Chair of Decision
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“Dynamics of Soil Processes” at the University of Hamburg, and also work closely with the junior research group “COLDSPOT”. PeTCaT aims at closing key knowledge gaps and at reducing uncertainties in carbon
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assigned to the research project "Randomization of Surrogates for the Quantification of Domain Uncertainty Propagation in Cardiovascular Models" as part of the Berlin Mathematics Research Center MATH+. The
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/statistics (experimental design, evaluation, uncertainty quantification) Excellent programming skills in Python (C/C++ is a plus); experience with HPC environments (e.g., SLURM) is welcome Interest in
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a unique opportunity to contribute to cutting-edge research on remote robotic control under network uncertainties, focusing on the development of fault-tolerant and adaptive control architectures
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implementation, High-Performance Computing experience, methods of Uncertainty Quantification Offer – What you can look forward to: A dedicated, international team from various disciplines, with collaboration
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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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application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and