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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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Department at Monash has a thriving research culture, and is ranked 33rd in the world in the latest QS rankings. Candidate Requirements The successful applicant will have an excellent academic track record in
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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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Antenna Design: Developing innovative antenna systems compatible with metal detector coils, optimized for tasks such as minimum-metal landmine detection and deep object detection. Low Power, Compact
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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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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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. 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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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