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to move beyond traditional group-level statistics and model individual variability more accurately. The dissertation will focus on the theoretical and algorithmic development of linear and nonlinear mixed
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. Despite significant progress, the fundamental mechanisms governing their formation remain only partially understood. Gaining deeper insight into these mechanisms is essential for improving control over comb
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, they may exhibit significant nonlinear large-signal behavior during disturbances, including current limiting, control mode switching, and loss of synchronism. In multi-machine systems, these transient
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limiting, control mode switching, and loss of synchronism. In multi-machine systems, these transient dynamics are further shaped by interactions among multiple GFM units and the surrounding grid strength
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combine electricity, heat, hydrogen, CO₂, and other energy carriers with greenhouse climate control, resulting in a highly coupled, nonlinear, multi-timescale dynamical system. Your work will focus
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) for exploration and inspection Soft and morphing aerial robots with pneumatic actuation Navigation in GPS-denied, cluttered, or dynamic environments Advanced Control and System Integration Nonlinear, adaptive, and
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industrial SBSP experts, the candidate will explore the nonlinear structural dynamics of LSSs to fully understand the complexity of their control. They will use this foundation to explore idealised and
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are eager to contribute to this rapidly developing field. Our research spans multiple disciplines, and we welcome applicants with backgrounds or interests in areas such as quantum optics, nanofabrication
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control algorithms that create value for multiple stakeholders, including EV users, aggregators, grid operators, and energy markets. – Develop advanced co-simulation platforms coupling distribution network
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opportunities? Do you have a background in Electric Power and/or Control Engineering, and are you interested in working at the intersection between both fields? As a PhD candidate with us, you will work toward