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emotions make individuals susceptible to the experience of pain. By identifying and applying a translational model of emotional flexibility, the neural networks that underly comorbidities of fear and anxiety
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. In this project we will study the functions of the rare coding variants using zebrafish and compare the results with mouse models of equivalent mutations and human post-mortem brain tissue
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from animal hosts (are ‘zoonotic’), yet it is hard to predict which pathogen species are likely to cross into human populations and why. This project will combine AI Large Language Models, extracting
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with no cure, and we urgently need new ways to understand and treat it. This exciting PhD project combines cutting-edge stem cell technology, 3D bioprinting, brain cell models, and advanced genomic
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to design an AI system that integrates scientific knowledge for early dementia modelling, based on large language models and causal inference. The project has two stages: first, to construct a causal
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and machine learning methodology to help deal with key challenges in developing such models in large-scale observational electronic healthcare record data. These models will be applied to important real
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mouse models, primary astrocyte culture, transcriptomics, and advanced imaging, you will identify the molecular signals linking neuronal JAKMIP1 dysfunction to altered astrocyte behaviour. Training across
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immunomodulatory compound, you will determine how it reprograms host lipid pathways to boost immunity and eliminate infection. Using lipidomics, zebrafish models and clinical samples, this research will identify
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. The student will use state-of-the-art in vivo electrophysiology, fibre photometry, fast-scan cyclic voltammetry, targeted optogenetic stimulation, behavioural tasks and computational modelling to record
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statistical approaches to characterise disease trajectories, develop risk prediction models, and identify factors associated with differential treatment outcomes. The findings will improve understanding of long