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Control is successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control
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methods for distributed state estimation in large and heterogeneous sensor networks, with particular emphasis on statistical model‑based approaches. As sensor systems scale up to vehicle fleets, drone
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systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups
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well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive
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Control is successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control
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research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division
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well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor fusion. The division has extensive
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application! We are looking for a PhD student in Medical Science, as part of the larger EU Marie Curie MCSA Doctoral Network STEM-CORE. Are you passionate about working with stem cells or stem cell-based
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are not limited to, numerical methods of high order, Discontinuous Galerkin methods, path conservative discretisations, efficient time integration, and energy / entropy stable methods. Curvilinear mesh