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. Yet, many stellar and planetary parameters remain systematically uncertain due to limitations in stellar modelling and data interpretation. This PhD project will develop Bayesian Hierarchical Models
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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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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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-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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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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opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions Exactly: A Bayesian Approach
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of machine learning, uncertainty quantification, and Bayesian modelling. They will provide complementary expertise to bridge agentic AI with real-world impact. What We Are Looking from You Background in
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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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close to the nest [1 ] but to better understand foraging, we need landscape level detail. The direction of the project can be tailored, but could include developing and applying Bayesian ML approaches
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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