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. Probabilistic rational models, implemented as either Bayesian models or deep neural networks, have been proposed as standard models, from low-level perception and neuroscience to cognition and economics. But
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will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental
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or a numerate discipline OR equivalent experience. Broad knowledge of probabilistic models, Bayesian inference and machine learning methods. Good knowledge of R, Python or both (links to project source
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impactful observation-based analyses informing forecasting ocean and climate models. Meeting these challenges, within the European HORIZON EUROPE projects GEORGE (https://george-project.eu/ ) and TRICUSO
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probabilistic modelling tools to help government, researchers and communities better understand and anticipate change community connectedness; including upstream predictors of factors which strengthen and factors
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around data science, econometrics and statistical modelling. For instance developing new probabilistic modelling tools to help government, researchers and communities better understand and anticipate
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successful appointee will be centrally involved in the delivery of the ARIA-funded Forecasting Tipping Points programme , and will work collaboratively with Professor Doug Benn (University of St Andrews) and
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(e.g. a transferable ML for flexibility forecasting) with a focus on designing a robust and scalable ML tool that can be deployed across our various pilot sites in the EU and the UK. The Research Fellow