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sensing techniques. The ultimate goal is to establish a framework for spatially extensive monitoring of European beech vitality under drought stress in Germany and Central Europe. This project offers
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) government, industry, and local NGO’s. Your main contribution will be the development of a spatially explicit agent-based model of the society of the Metropolitan Region of Amsterdam, simulating circular
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to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing
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: Quantitative analysis of experimental data and description of spatial structures in crowds (e.g., Minkowski functionals, Voronoi analyses, clustering methods) Comparison of physical structural analyses with
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Germany (https://ngs-kn.de ). Its primary technological focus is on implementing innovative methods for single-cell and spatial sequencing, as well as bulk short and long-read sequencing applications. With
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(derived from AI-supported monitoring and analysis of sources such as satellite imagery, acoustic sensors, and camera traps) can inform spatial planning and decision-making for solar and wind energy
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ecological modelling, spatial analysis, and interpretation of biological datasets. Demonstrated leadership of complex abalone field programs. Experience supervising HDR students, technical staff, and early
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Scheduled Hours 40 Position Summary Performs data management and/or data analysis for investigators using statistical packages. Assists investigators in the design of experiments, clinical trial
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research that links question answering, knowledge modelling, geo-spatial analysis, and workflow construction. This PhD position focuses on developing a semantic model of the diverse geodata sources in a map
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may include but are not limited to: Introduction and Intermediate GIS, Spatial Analysis, Cartography, Outdoor Field Skills, Adventure Programming, and Recreational Lands Management for Sustainable