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Field
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analysis: Applying geospatial methods (GIS mapping, geographically weighted regression, spatial clustering) and temporal approaches (time-series analysis, distributed lag models, case-crossover designs
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for NCDs. This will involve: Spatial analysis: Mapping and modelling environmental exposures at fine spatial resolution using GIS tools, geographically weighted regression, and spatial clustering techniques
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, and community resilience across vulnerable deltas. We welcome applicants with quantitative aptitude and curiosity about rivers, hazards, and sustainability (training provided in GIS, coding, and
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., 1st March 2026). Specific Requirements Solid practical experience with GIS (e.g., QGIS, ArcGIS), including spatial data processing and visualization; Experience with data analysis using Python, Matlab
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objectives (e.g. geography, biology, epidemiology and public health). The person recruited will have competence in statistical analysis and GIS, experience or at least interest in carrying out field work and
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monitoring. Responsibilities Drive forward the department’s analytical and statistical expertise in remote sensing, LiDAR, AI tools, GIS, and spatial modeling. Take a leading role in developing digital tools
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, Urban Studies, Urban Analytics, Environmental Science, Computer Science, Architecture, or an appropriate master’s degree. Familiarity with Python/R programming, GIS and spatial analysis (e.g., ArcGIS
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monitoring. Responsibilities Drive forward the department’s analytical and statistical expertise in remote sensing, LiDAR, AI tools, GIS, and spatial modeling. Take a leading role in developing digital tools
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or similar areas, and fully comply with the following requirements: The doctoral degree must have been obtained at least 1 year ago; Proven experience in GIS environment analysis (QGIS, ArcGIS, R), statistical
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reporting of flood events. Using GIS, AI, and time series analysis, you will reveal how climate risks and housing dynamics intersect and how patterns may evolve under climate change. Leicester and