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radiocarbon dating and Bayesian modelling. The postdoctoral researcher will contribute to an ongoing research project, “Milestone”, headed by Associate Professor Sarah Croix. The appointment begins on 1 April
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medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
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on the development of mortality surveillance systems from Tribal health departments. This project develops innovative Bayesian hierarchical spatio-temporal models to integrate multiple surveillance systems, correct
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of gradient flows using reinforcement learning (Studentship code MSP107) Dynamic Bayesian modelling of endurance sports (Studentship code MSP108) Data structures and postprocessing for phylogenetic MCMC
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within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts. Methods include agent based/individual based modelling, SEIR modelling
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working within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts. Methods include agent based/individual based modelling, SEIR
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from relevant experts, to develop and evaluate Bayesian approaches for simultaneously accounting for multiple sources of uncertainty Main Responsibilities: Prepare and revise statistical analysis plans
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opportunities for better design. AI-driven optimisation offers a promising parallel route forward. Techniques such as Bayesian optimisation have already proven successful in related contexts, such as optimising
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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
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of the research include: (1) Designing and executing methods to integrate data from different sources, including developing a Bayesian Hierarchical Modeling framework; (2) using integrative modeling approaches