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adherence to established protocols and timelines. This includes contributing to project planning and risk assessment Design, organise and facilitate workshops and training courses to disseminate research
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research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data Analytics and Management; (iii) Computer Vision and Pattern Recognition; and (iv
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research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv
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are important, leading to different models being used. However, in recent years model topologies for automatic speech recognition and many other speech processing tasks have started to converge - driven by
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. The research will support the development of innovative construction solutions aligned with circular economy principles, decarbonisation of the construction sector, and sustainable material design. 3
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to investigate how to design AI artefacts, including user interfaces and algorithms, through participatory approaches that actively involve stakeholders (e.g., technology designers and actors from
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jointly learn from images and text, most current systems are still limited in three important ways: they primarily rely on statistical pattern recognition rather than structured clinical reasoning
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building. This PhD fellowship is associated with the centre’s first research cluster, which focuses on Hybrid Intelligence. A key objective of this cluster is to investigate how to design AI artefacts
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recognise subtle, often unconscious, signals of stress. It will enable target groups to react more adequately in stressful moments by improving the early recognition of these signals in daily life and by
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, positioning the gut microbiome as a potential driver of menopause-related symptoms and longer-term risks for metabolic and age-related disease (e.g. dementia). Despite the growing recognition