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position for candidates interested in interpretable AI, stochastic optimal control, deep learning and high-impact research in sustainable mobility. About us The position is located at the Systems and Control
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qualifications: a PhD or equivalent research qualification within chemical engineering or water and environmental engineering In-depth knowledge in process engineering and process automation Knowledge and skills
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of Stockholm Trio (KI, KTH, SU) and is the only SciLifeLab site that co-localizes researchers from multiple universities under one roof. By working together Stockholm Trio has been able achieve a significant
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well as the performance of active flight control systems remain underexplored. Addressing these gaps is essential for the success of this technology. This research project aims to support the development of safer, more
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areas, engaging in both theoretical and experimental research in: Data-driven and learning based control - Data-driven adaptive motion planning - Cognitive reasoning, symbolic knowledge representation
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monitoring. These applications rely on remote sensors to capture PCs and wirelessly transmit them to edge servers for downstream tasks, such as registration, i.e., aligning multiple PCs within the same 3D
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measurements to the results of existing techniques using backscatter to quantify forest attributes through synthetic aperture radar imaging. The overall project, spanning multiple institutions, aims to produce a
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automated planning, reinforcement learning, logic or combinatorial optimization. Furthermore, candidates should have excellent study results, very good programming skills and high proficiency in oral and
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higher availability. Through well planned maintenance, external and internal operational risks can also be controlled and minimized. The subject area/division of Operation and Maintenance Engineering is
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-quality infrastructure such as laboratory facilities for rocket propulsion, small satellites, asteroid engineering, and space avionics. Subject description Space systems includes systems for control