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and Analytical Skills Competence in data visualization to communicate complex results to scientific and policy audiences. Knowledge in geospatial analysis or GIS for linking environmental variables with
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event. You will join a diverse community of colleagues based in Newcastle in our Civil and Geospatial Discipline, supported by Dr Anna Murgatroyd with expertise in water resources and hydrology. In
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variables derived from high‑resolution aerial imagery, geospatial datasets, and AI‑assisted land‑cover classification Additionally, national diabetes registries will be used to map local type 1 diabetes
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National Mapping Service, the research will examine the early implementation of an AI-driven automation in geospatial mapping. OS is integrating AI tools to accelerate map updates and reduce costs, while
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at the interface of machine learning, deep learning, geospatial AI, causal modelling, and digital health systems. Your Role You will develop the core AI and data-driven models that transform large-scale
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learning, geospatial AI, causal modelling, and digital health systems. Your Role You will develop the core AI and data-driven models that transform large-scale exposomic and health data into actionable risk
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and/or R for data analysis; Experience in geospatial modelling and workflows. Fluency in spoken and written English; Valued competences: Knowledge of remote sensing applied to ecological and landscape
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in Python and affinity with large geospatial datasets. Interest in interdisciplinary research at the interface of geoscience, engineering, and societal impact. Good communication skills and willingness
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute