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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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. Your expertise includes machine learning techniques such as Bayesian optimisation, and you’re comfortable working with experimental data, high-performance computing environments, and (ideally) thin film
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
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, Joshua W. and D.L. Dowe (2005). ``Minimum Message Length and Generalized Bayesian Nets with Asymmetric Languages'', Chapter 11 (pp265-294) in P. Gru:nwald, I. J. Myung and M. A. Pitt (eds.), Advances in
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networks, Bayesian inference, computational neuroscience, mathematics.
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the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms
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for the prediction task, such as predicting the bioassay of a given chemical network. One of the approaches that will be considered will be the Bayesian information-theoretic Minimum Message Length (MML) principle
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back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum message length (MML) approach (Wallace and Boulton, 1968
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum