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(UA). This fully funded PhD position offers a unique opportunity to contribute to the future of pandemic resilience through scenario analysis, clinical data collection strategies and implementation
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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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of inflow and turbine setpoint changes (e.g. grid curtailments) on wind turbine component loading (b) the effect of wind turbine spacing on wind turbine farm loading (c) the differences in loading
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include regulations, compilations of local legislation and commentaries thereon, as well as rulings by municipal courts. You will conduct research in archives. Based on an analysis of source material
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. The candidate will conduct research in archives. Based on an analysis of source material, the strategies developed to reconcile the interests of multiple bondholders will be examined. Specific attention will be