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largely undeveloped. Addressing this challenge will be the central objective of your PhD research. Responsibilities and qualifications You will develop a physics-based modelling framework for bearingless
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estimation, and performance prediction. Build computationally efficient models suitable for monitoring, performance prediction, optimization, and control, and evaluate their accuracy, robustness, computational
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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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, experimental, and modelling datasets related to physical oceanography, bentho-pelagic coupling, and carbon export. • Investigate the mechanisms controlling carbon export from surface waters to the deep ocean
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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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BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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. Control and dynamic systems: A solid understanding of control theory, dynamic modelling and autonomous systems. Experience with trajectory tracking, path following, model-based control, state estimation
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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heat integration in integrated Power-to-X systems. You will develop and apply physics-based process models that describe the behavior of Power-to-X plants under varying operating conditions. This