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learning by using Bayesian learning principles. Among other things, Bayesian learning gives AI systems the ability to quantitatively express a degree of belief about a prediction or statement. By bridging
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funding. Candidate Requirements The successful candidate will require a proven track record in research fieldwork and historical methodology. In its assessment, the selection committee will prioritise
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indicators beyond current proxies. High-Speed Rail (HSR) and National Spatial Optimisation Examine how HSR infrastructure reshapes urban and regional population distribution, and develop a multi-objective
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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the optimisation strategies to enhance the performance of complex machine learning models such as deep learning model and large language model. Applicants need to have strong background and track records of research
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objectivity and consistency. Recent studies have highlighted the potential of computed tomography (CT) scans to provide objective markers of frailty. Metrics like Psoas Muscle Density (PMD) and Kidney to Body
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tracking blood glucose responses to meals and lifestyle factors, the project will identify individual patterns and predictors of glucose variability. Using this detailed data, tailored dietary
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. Objectives Overcoming the limitations of classical acoustic communication systems: We will investigate joint transmitter and receiver designs for underwater acoustic communication systems. We will identify
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in decarbonising the steel sector. This research aims to investigate the impact of slag and ore impurities on molten salt electrolysis for sustainable iron production. Research objectives: Assessing