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highly motivated researchers in all areas of the field, including but not limited to: quantum algorithms and complexity; quantum information theory; quantum cryptography; quantum information in many-body
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complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms will be tested and
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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Models, LLMs, etc. PhD and PostDoc Positions in Visual Computing & AI The Visual Computing & Artificial Intelligence Group at the Technical University of Munich is looking for highly motivated PhD students
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correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de)confinement in string-net models - Quantum field theory
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, depending on the geographical and economic context. It will include a deep dive on the potential of Ukraine to become a green hydrogen hub, leveraging geo-spatial energy models run by project partners. As
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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed
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. 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 for livestock
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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 for inverse
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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