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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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-methods framework for participatory analytics that integrates climate and health data, intersectional multi-level analysis of vulnerabilities, and participatory action research. A central aim is to
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. Demonstrated proficiency in GIS, remote sensing, spatial analysis, or other applied geographic techniques. Preferred: PhD degree in Geography, Geosciences, Computer Science, Environmental Science, or a closely
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developing approaches to leverage spatial data to better understand evolutionary histories. More information about the lab and their work can be found by visiting https://federlab.github.io/ About the
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details. Read about the PhD education at SLU at https://www.slu.se/en/study/programmes-courses/doctoral-education/ Academic union representatives: https://internt.slu.se/en/my-employment/employee
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https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-july-2025-scales/t37-b.pdf . A reasonable full-time estimate for this position is $76,700 - $97,700 Percent time: 100
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high content imaging, multimodality in vivo imaging, proteomics, spatial and single-cell transcriptomics. As part of King’s Health Partners, we have an excellent environment for basic-clinical
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of large spatial and temporal biodiversity datasets. Since almost 20 years the Rhine-Main-Observatory (RMO; https://www.senckenberg.de/rmo/ ) has been part of the German LTER network (https://www.ufz.de/lter
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to communicate in English, both spoken and written Knowledge and experience of independently performing spatial omics (data collection and analysis) Knowledge and experience of independently performing
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digital twins require more than visually plausible models: they require analysis‑ready geometry for simulation and decision support. This PhD project develops methods to generate LOD3 urban surface meshes