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Field
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, geographical and theoretical approaches including, among others, network theories, connected history, reading history, medical humanities, material culture studies, postcolonial perspectives, and digital
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are offering a fully funded PhD position in the field of Physics-informed Learning-based Control. This interdisciplinary research area bridges control theory, machine learning, and physics-based modeling
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programs. Alternatively, Mathematics, Computer Science, Computer Engineering, Electrical Engineering, or a similar field; Strong mathematical background: basic knowledge of graph theory and excellent
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that allow you to: understand and apply quantitative (statistical, econometrical, analytical) methods, understand regulation-related theory and practice; motivation to do high quality research with the aim
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status pursuant to the German Social Code IX (SGB IX) will receive priority for employment. Please submit your detailed application with the usual documents (Curriculum Vitae, cover letter, list
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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of advanced theory formulation and method development as well as systematic integration of theory and empirical research. The student will be trained in the ICS. The Interuniversity Center for Social Science
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shall be developed. The work will be in close collaboration with the PhD student working on fundamental solid-state theory of the same materials. Your tasks Your job tasks includes the following
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design. Their research contributes to the theory and practice of sensory and cognitive communication and augmentation design and the section is unique for its cross-disciplinary approach to design for real
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that enable interpretable models to learn from deep representations. In this project, the researcher will develop theory and algorithms for (hybrid) model selection that allows to exploit domain knowledge