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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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polycrystalline material during plastic deformation in order to eventually predict the manner in which materials deform and fail. As a first step, we wish to infer a distribution of the directions of deformation
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of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological
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horticultural data from digital images by analysing their content. The aim is to infer information that might not be immediately apparent, even to the photographer, in order to improve our understanding of animal
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networks, Bayesian inference, computational neuroscience, mathematics.
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Login Recently added Development of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability
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tracking schedule. Collaborate with mission teams to meet tracking objectives. Perform logging, data trending, and operational safety monitoring. Support testing, troubleshooting, and system diagnostics with
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candidate will have demonstrated expertise in computational methods in statistics, particularly in simulation-based inference methods, or Monte Carlo methods, and their associated theory or applications
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. This will be achieved through frequency domain and time domain state and parameter estimation techniques to infer model states and parameters in real time to simultaneously track the anaesthetic brain states
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on Artificial Intelligence and Statistics (AI+STATS 2001), pp253-260, Key West, Florida, U.S.A., Jan. 2001 P. J. Tan and D. L. Dowe (2003). MML Inference of Decision Graphs with Multi-Way Joins and Dynamic