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. Scientific Aims The project will: • Build hierarchical Bayesian frameworks to jointly infer stellar population parameters and individual stellar properties. • Combine asteroseismic, spectroscopic, and
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infinite-dimensional (e.g., space-dependent) parameters and state variables. Inferring these parameters and/or states from large amounts of possibly high-resolution data leads to computationally intensive
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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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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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-represented backgrounds. The objective of the research project is to perform Bayesian inversion to characterise the velocity field of 3D partial differential equations describing brain fluid and solute movement
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Your Job: This research primarily seeks to incorporate advanced neuron models, such as those capturing dendritic computation and probabilistic Bayesian network behavior, into unconventional
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modalities Developing and applying polygenic risk scores and causal inference models to predict disease onset, progression, and treatment response Implementing machine learning and statistical genetics
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for individuals that are interested in pursuing a PhD in economics or finance. The chosen candidate will also gain valuable experience in the application of machine learning and Bayesian inference methods
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, optimization, dynamic systems, decision theory, Bayesian inference) ● Is motivated to apply these methods to ecological, evolutionary, and conservation systems; ● Is comfortable with uncertainty, modeling