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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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the ParkMobile app., assist with special events as needed, direct traffic as part of strategic overflow control, and greet customers and assist with their needs. Additional duties include serving as parking
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to aerospace, defense, semiconductor, energy, and other industry sectors that are well represented in the region, one of the most economically robust in the nation (learn more at https://poly.engineering.asu.edu
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project is described here: https://seddit.se/project/robust-large-scale-estimation . As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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optical control and excitation with the goals of improving robustness and coherence. In the FWF project BRAIDS we are working towards the generation of time-bin entanglement via dark exciton states. In our
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) amongst others. The role-holder must maintain robust internal controls and oversee external and internal audit processes, ensuring transparency, accountability, and value for money. They are expected
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Postdoctoral Fellow to join the Tang Lab. The Tang Lab (https://tangxinlab.org/ ) works at the intersection of AI-driven automation, self-driving laboratories, and scientific discovery, in close collaboration
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 7 days ago
: This grant aims to develop methods based on reachability analysis to design robust MPC controllers for the final approach of a tethered spacecraft for active debris removal. This grant will investigate
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application! We are looking for a PhD student in automatic control at the Department of Electrical Engineering (ISY). Your work assignments We are currently looking for a PhD student to conduct research
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hardware constraints, improve system control, and unlock new modes of problem-solving that surpass classical approaches. The ML-QSIM project is built upon a robust multi-node and multi-regional structure