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on modelling and controlling electrified industrial thermal systems under real-world conditions. The work is embedded in a collaborative research project with industrial partners, providing access to realistic
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years. Your work tasks This PhD project focuses on the design and control of energy-efficient hydraulic systems with integrated safety functionalities. The overall objective is to develop innovative
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behaviour for system monitoring, state estimation, and performance prediction. Build computationally efficient models suitable for monitoring, performance prediction, optimization, and control, and evaluate
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on designing and evaluating cognitive support interventions, working with stakeholders to co-design techniques and assess their impact through controlled studies. This suits candidates with strong user-centred
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investigate how sensor data can be fused to improve navigation, obstacle awareness, vehicle state estimation, guidance and mission reliability. Propulsion-control co-design: Studying the coupling between
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applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results into applications in
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and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and electrotactile
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optimization, techno-economic assessment and model validation. The research will also examine the coordinated operation and control of Power-to-X processes, electrolysers and energy-storage systems in
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported