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for classifying user activity in office buildings using power consumption data, with a focus on probabilistic approaches such as Gaussian Processes that provide principled uncertainty quantification
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discovery and inference, with an emphasis on robustness, scalability, uncertainty quantification, expert knowledge integration, and multi-scale causal abstraction and representation learning. Your Job How are
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
. Data-driven methods, for instance for inverse parameter identification or uncertainty quantification in fracture mechanics datasets, are not an end in themselves, but a compelling extension where they
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, including uncertainty quantification, probabilistic modeling, and learning from noisy or incomplete data is a plus Practical experience with High Performance Computing (HPC) systems is an advantage Your
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
, how it can be extracted, and how confidently conclusions can be drawn. Develop and apply approaches for uncertainty quantification, robust inference, and validation of biomedical imaging results. Work
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Experience in one or more of the following areas: object detection and segmentation, multi-object tracking, time-series analysis, probabilistic modeling and uncertainty quantification, real-time or streaming
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physics, multiscale modeling, and uncertainty quantification. The Multiscale Modeling of Fluid Materials group at the Technical University of Munich is looking for talented and ambitious scientists