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Advanced strongly typed languages like Haskell and emerging type systems like refinement types (as implemented in Liquid Haskell) offer strong guarantees about the correctness of programs. However, when type errors occur it can be difficult for programmers to understand their cause. Such...
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, they will have prior knowledge of infectious disease modelling, Bayesian inference methods and optimisation methods. They will have a developing research profile, with a demonstrated ability to publish
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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Psychology/Cognitive Science A track record in research excellence evidenced by peer-reviewed journal articles published in high quality journals relative to opportunity Experience in cognitive psychology
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nodes and chemical bonds as edges. Analysis these networks are important as they may provide AI-based approaches for drug discovery. This project will focus on representing and inferring chemical or
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Psychology/Cognitive Science A track record in research excellence evidenced by peer-reviewed journal articles published in high quality journals relative to opportunity Experience in cognitive psychology
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the timing, scale, and rate of mammal declines in Australia. They will use critical inferences of past demographic change and high-performance computing to disentangle the ecological mechanisms that were
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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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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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consumer facing tools pursue and develop a translational research program related to the evaluation of treatment modalities in fertility treatment using modern causal inference methods applied to real-world