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Synergies between humans and AI-enabled systems are relevant in situations involving complex and high-stakes decision making. The effective integration of humans and AI can be based on knowledge
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PhD Knowledge-Infused AI for Human-Technology Integration (V24.0004) « Back to the overview Job description Synergies between humans and AI-enabled systems are relevant in situations involving
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-sectional and longitudinal econometrics and machine learning techniques to determine the relationship between environmental stressors and population health. This project is part of a larger project ECOTIP
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PhD position on the topic The Relationship between Health and Environment (V24.0118) « Back to the overview Job description Project description While the association of adverse environmental
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addition, it will employ cross-sectional and longitudinal econometrics and machine learning techniques to determine the relationship between environmental stressors and population health. This project is
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operation and control of physical systems, in a form of mixed physical-digital-human system. Recent research has targeted the development of Human-Centred Digital Twins, as the Digital Twinning of physical
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PhD position on Human-Centred Digital Twins in Industrial Work Environments (V24.0003) « Back to the overview Job description Digital twins enjoy significant take-up in a wide range of industries
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PhD position Dynamic analysis and human vibration perception of hand held (V23.0732) « Back to the overview Job description We are looking for a candidate to undertake research in the field
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at an early stage before any prototypes are made. If unpleasant human perception being predicted, then the vibration levels can be reduced by design modification for healthy products. First, a numerical model
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designed and deployed in ways that align with values such as transparency, explainability, and trust. This research will delve into the intricacies of AI-human collaboration in high-stakes environments