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– Transition and spatial recomposition (Service Learning) (12 hours Th, 20 hours Pr), Master’s in Geographical Sciences – Global Change programme. GEOG2028-1 – Introduction to spatial planning: planning systems
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preprocessing; Integration of geospatial and soil data into databases. Data processing and analysis: Application of geoprocessing and spatial analysis techniques; Development and calibration of predictive models
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candidate will be encouraged to independently explore large-scale omics datasets (e.g., bulk and single-cell RNA-seq, spatial transcriptomics, proteomics) to identify and prioritize novel biomarker
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 12 hours ago
nebulae, protoplanetary disks—but also from exoplanets and galaxies. The data and tools will enable interpreting observational data from NASA missions, notably, JWST, which is now spectrally and spatially
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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successful candidate will work in the AI in Medicine Lab, applying machine learning to cutting-edge problems in cancer genomics, transcriptomics, spatial transcriptomics, and large-scale bioinformatics
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data. This position offers an exciting opportunity to work at the intersection of cancer biology, spatial multi-omics, and artificial intelligence. More information: https://digitalhealth.tu-dresden.de
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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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Memories in Post-Migrant Society” research unit Collaboration in the project council Where to apply Website https://karriere.th-koeln.de/job/view/1515/postdoctoral-researcher-m-f-d-in-the… Requirements
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working knowledge of GIS platforms (e.g., ArcGIS, QGIS) and spatial data analysis techniques. Training or demonstrated experience in remote sensing, spatial data collection, and thematic mapping