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Field
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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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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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involved in Net Zero which is a world-leading centre in science and technology research at King’s. Net Zero aims to focus on research for decarbonising our economy and society, and addressing key
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is involved in Net Zero which is a world-leading centre in science and technology research at King’s. Net Zero aims to focus on research for decarbonising our economy and society, and addressing key
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is involved in Net Zero which is a world-leading centre in science and technology research at King’s. Net Zero aims to focus on research for decarbonising our economy and society, and addressing key
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field. Preference will be given to candidates with: Previous experience in machine learning-related aspects of computational neuroscience, specifically with approximate Bayesian inference, and function
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open-ended position. Applicants are invited from any area of applied statistics, including statistical or actuarial data science. Those working in actuarial science, Bayesian statistics, statistical
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include Bayesian data analysis, nonparametric statistics, functional data analysis, spatio-temporal statistics, and machine learning/artificial intelligence. Many of our projects involve dynamic processes
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model fitting, including Bayesian model fitting. Experience of management and analysis of large multidimensional real world data sets. What we can offer you The opportunity to continue your career at a
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projects, including: The post-holder will run numerical models that simulate the dispersion of greenhouse gases through the atmosphere. These models will be used, in Bayesian inference frameworks