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for treating brain disorders? In this PhD you will work with datasets of neuronal activity in animals and humans. You will apply computational approaches to describe spatial and temporal patterns across
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expertise in single-cell spatial analysis and collaborations with leading epidemiologists, we have collated unique data resources that will enable us to characterise the link between obesity and the breast
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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community engagement. In this role, you will: Contribute to research on ecological and spatial data for urban environments: Conducting fieldwork, data collection and analysis related to urban air quality and
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approach including empirical data analysis, experiments, and theoretical modelling to develop science-based management strategies for the restoration of woodland ecosystems. We will collect, and collate from
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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an integrated approach that combines spatial analysis and field-based data collection, this project will assess how canopy cover varies across walking routes in Reading and which communities benefit from
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ideal candidate will have an interest in ecological modelling, spatial analysis, and conservation planning, with experience in ecological fieldwork or quantitative data analysis being advantageous. Full