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that come along with large-scale experiments. We offer leading interdisciplinary research between domain research fields and computer/data science or applied mathematics; research at world-leading, large
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and optimisation techniques, to provide efficient, scalable and robust solutions to state-of-the-art, large-scale discrete/combinatorial problems. Detailed information about the group can be found
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and analyzes quantitative and qualitative data on the firms’ pro bono efforts related to human rights, environment and climate change, and migration. PROBONO seeks to understand these dynamics and their
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networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In this project
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. - Neural networks and machine learning strategies for the analysis of scattering data. Large amount of scattering data obtained in our group requires development of the advanced analysis techniques. In
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
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our research and whether it may fit your interests, please read some recent papers by our lab before you apply. Additional Information CISPA and the University of Stuttgart have a large interest in
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generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. The Macroscopic Quantum Optics (MQO) Group at the Department
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview A major