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and objectives Vision-language-action models (VLAs) Investigate VLA models and multimodal representations that connect visual observations and language instructions to robot behaviour, including
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on developing and studying privacy-preserving methods, such as differential privacy, Bayesian privacy, federated learning and synthetic data. The aim is to enable meaningful analyses, such as identifying disease
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration, experimental testing, or hardware-in-the-loop
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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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’ Cognitive Autonomy in Human-AI Interaction’). Research objectives This project develops methods to detect changes in users' cognitive load and designs digital interventions that support cognitive autonomy in
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of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration
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exploited by intelligent physical systems, such as robots, vehicles, and distributed autonomous agents, to perceive and interpret their environment and support timely physical action. A central objective will
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methods and examine challenges concerning both private and public sectors. It is our objective to become a world class leader in excellent research and high-quality teaching. We further strive to provide
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political objectives, which is further complicated by the development of new technologies and societal demands for sustainability. Within this context, the PhD application should reflect an independently