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areas of sustainable intensification of agriculture, climate mitigation and adaptation, livestock systems, and healthy and sustainable diets, providing analysis and insights aimed at helping to shape
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-index tomography experimental setup, including optical alignment, calibration, and performance evaluation. Conduct quantitative performance analysis of the system, including spatial resolution, phase
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. Your team You will collaborate with GRS colleagues who have expertise in methods and tools for spatiotemporal analysis of complex land systems (including agent-based modelling), spatial data
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across different spatial and temporal scales, from building-level energy demand to district-scale interactions and their integration with wider energy networks. PhD Position in Hierarchical Graph Neural
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: Experience in method development, working with spatial data, and GIS Experience with univariate and multivariate analysis and working with large datasets Experience with working independently and organizing
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(landscape) ecologist with a broad, interdisciplinary interest with experience in spatial analysis of interactions between land use and biodiversity. Your work includes teaching courses in environmental
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change. Experience in quantitative methods, spatial analysis, or handling large datasets would be valuable, but full training will be provided in climate modelling, statistical downscaling, and health
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, College of Department: Data Science Rank: Associate Professor Annual Basis: 9 Month Application Deadline October 31, 2025 Required Application Materials Candidates are asked to apply online at https
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, including knowledge of AutoCAD and GIS (ArcGIS or QGIS) software; 6. Knowledge of spatial analysis methods; 7. Experience in university teaching; 8. Fluency in Polish—ability to communicate clearly and
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques