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combines spatial point process models for the emergence and arrangement of objects (including birth-death dynamics, merging, and non-overlap constraints) with methods from shape analysis, in particular
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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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(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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-bathymetric surveys from diverse national and global data sources; Analysis of local, regional and global wave data; Determination of theoretical depth of closure and its temporal and spatial variability
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in
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Internal Number: JR91931 Scheduled Hours Empty heading 40 Position Summary Empty heading Performs data management and/or data analysis for investigators using statistical packages. Assists investigators in
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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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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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) 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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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