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implement machine learning algorithms to model and analyze dynamic phenomena in milling processes Explore and apply Physics-Informed / Physics-Guided Machine Learning approaches Design and develop cloud-based
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-native wireless communications and networking, specifically developing context-aware multimodal Generative AI (GenAI) models, scalable mixture-of-experts (MoE) at the network edge, and multi-agent
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of nonlinear PDEs or the development of new solver- or coupling-methods incl. their convergence analysis, but also modeling and simulation aspects across a wide range of fields - from biomechanics and geophysics
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on optimal sequential decision-making in critical healthcare. The project aims to develop mathematical foundations for rigorous, interpretable, and data-driven decision models that integrate: Markov Decision
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Your Job: As part of this master`s thesis, the agent-based energy market simulation ASSUME should be expanded to include the local neighborhood. The goal is to further develop the existing
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theory, ideally with a focus on mathematical approaches to quantum information theory, quantum algorithms or quantum complexity theory, or alternatively on other aspects of quantum information in
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(Berlin) in a close partnership with the Forschungszentrum Jülich, contributing to algorithm development, computational tool implementation, and validation with experimental partners (TU Graz and
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/en/tms/jobs/ We are seeking two Research Associates (f/m/d) to work on the methodological development and application of advanced electronic-structure approaches, with the opportunity to pursue a PhD
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dynamic systems, control engineering, and applied mathematics? Do you want to develop cutting-edge control algorithms for the security and resilience of cyber-physical systems? We welcome you to apply for a
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constraints in local energy market simulations. The developed methods shall then be evaluated in suitable scenarios with respect to selected technical, economic, and system-related indicators. This leads in