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interests in the areas of applied and pure mathematics, and statistics. In Statistics, the School has research strengths in Bayesian and Monte Carlo Methods, Biostatistics and Ecology, Combinatorics, Data
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Processing/Control Path Planning/Trajectory Planning Multi-Target Tracking/Multi-Object Tracking, Bayesian Filtering, Radom Finite Set filters or closely related multi-target tracking approaches in radar
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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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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demonstrate strong statistical analysis and manuscript preparation skills, a strong track record of refereed publications, and a demonstrated trajectory of leadership capability. You should be able to work
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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 Explainability and Compact
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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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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
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: 04EX783), pp439-444 Frey and Osborne (2013) Frey and Osborne (2017) P. J. Tan and D. L. Dowe (2003). MML Inference of Decision Graphs with Multi-Way Joins and Dynamic Attributes , Proc. 16th Australian