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will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how environmental factors and antifouling technologies
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of biofouling processes in marine environments. This role will focus on developing and applying Bayesian statistical models to investigate and predict biofouling patterns to enhance our understanding of how
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-dimensional statistics, semiparametric/nonparametric methods, change-point problems, signal processing, Bayesian statistics and machine learning. Candidates must have a PhD in Statistics, Biostatistics, or a
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community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the best people come to do their best work
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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interpretations, in this project, we will use Bayesian statistics and phylogenetic methods to evaluate whether the timing of CSP clade evolution and HGT events are consistent with the oxygenation timeline
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around us? At Maastricht University, you will investigate how individuals differ in predictive processing by combining behavioural and neural testing with computational modelling. Together with colleagues
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environment, of engineering AI solutions to problems (especially neural networks or large language models) and/or applying data science techniques (such as Bayesian or similar statistical modelling). You should
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-development and refinement of conceptual models; devising management scenarios; building network models in one or more platforms (e.g., loop analysis/qpress; fuzzy cognitive maps/Mental Modeler; Bayesian belief
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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will