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Field
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the student to guide the research, but preliminary ideas include: Exploring whether suggested discharge limits derived from single organism experiments are protective of microbial communities; Using Bayesian
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under uncertainty (Studentship code MSP106) Learning to sample: Meta-optimisation of gradient flows using reinforcement learning (Studentship code MSP107) Dynamic Bayesian modelling of endurance sports
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receive training and skills in some of the following: meta-barcoding, stable isotope analysis, trophic-web analysis, Bayesian statistics, wet-lab experimentation – respirometry, fieldwork. Previous
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, stable isotope analysis, trophic-web analysis, Bayesian statistics, wet-lab experimentation – respirometry, fieldwork. Previous experience in any of these areas is useful but not essential. Diving
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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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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solvers, or the use of program synthesis, for example, for superoptimization. While we have a clear objective, the path towards this objective is flexible. All our work is developed in close collaboration
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-supervised learning, and few/zero-shot techniques — the student will adapt models to ecological data. Bayesian deep learning and ensemble methods will be explored for trustworthy uncertainty estimation
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maximum of ONE student per project. This process will ensure an excellent fit of student to project and also an excellent strategic fit of the project within the faculty. Project titles: Bayesian methods