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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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your career in academia. The Department of Econometrics & Business Statistics at Monash University is a global powerhouse with a dynamic team of approximately 50 leading academics and a similar number of
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of Violence against Women (CEVAW) plays a vital role in analysing and visualizing statistical data to support research on violence against women. They provide advanced analytical services, consult with
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should have: Doctorate in relevant discipline, proficient in statistical analysis and manuscript preparation Strong interpersonal skills, teamwork, positive attitude Teaching experience, ability
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or methodologies you have experience with, especially in the context of behaviour change research (e.g. statistics, evidence reviews, behaviour identification and prioritisation, interventions, etc) How you manage
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: Opinion and subjective probability in science: Oxford University Press; 1991. French S. Group Consensus Probability Distributions: A Critical Survey. In: Bernardo JM, editor. Bayesian Statistics 2. Oxford
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This project aims to explore techniques for characterising the complexity of statistical models. By complexity we refer to the ability of a model to learn patterns, and to potentially generalise
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based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
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: 10.1093/comjnl/bxm117 D. L. Dowe (2011a), "MML, hybrid Bayesian network graphical models, statistical consistency, invariance and uniqueness ", Handbook of the Philosophy of Science - (HPS Volume 7
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), "Message Length as an Effective Ockham's Razor in Decision Tree Induction", Proc. 8th International Workshop on Artificial Intelligence and Statistics (AI+STATS 2001), pp253-260, Key West, Florida, U.S.A