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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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, anxiety, chronic pain and movement disorders. By integrating dynamical systems theory and control theory with machine learning, you will work toward a generalisable, adaptive infrastructure for personalised
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, ensuring stable operation even as system dynamics evolve. Recent advances in Modular Multilevel Converter (MMC) topologies, along with developments in battery and supercapacitor technologies, create new
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of methane dynamics in rapidly changing ecosystems and contribute to improving predictive models of future methane emissions. Field sampling will focus on regions where methane cycling is still poorly
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD has established the Collaborative
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discharges. Complicating the understanding of these systems is the fact that predicting their evolution requires an understanding of multi-component transport phenomena, multi-phase evolution dynamics, solid
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real-world applications? Are you fascinated by how the local dynamics of nearest neighbour models can determine the macroscale behaviour of a system? Do you want to understand how matter self-organizes
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of public spaces, their long-term management is just as important. Most of a public space’s life happens after it's built—and the quality of that life depends heavily on how it is governed. This PhD project
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport