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Earth Observation data analysis and/or spatial modeling Proven ability to publish in high impact peer-reviewed international journals Experience with machine/deep learning / AI applied to environmental
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performing computational analysis of cutting-edge sequencing datasets. S/he will be in charge of the analysis of single-nucleus RNA/ATAC-seq and spatial transcriptomics data from brain tumor patient samples
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Systems (GIS) and large-scale spatial and environmental pattern analysis. They will also be responsible for participating in soil sampling teams and in the design of large-scale monitoring networks. With
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 20 days ago
: Advanced degree (PhD) in statistics or bioinformatics relevant field. Experience with analysis in R. Essential Skills: Degree in statistics or bioinformatics relevant field. Three or more years of analysis
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3 Apr 2026 Job Information Organisation/Company Nantes Université Department LPG UMR-CNRS 6112 Research Field Geosciences Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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multimodal expansion (“ImmunoPixel‑seq”). Work includes NGS data processing, spatial barcode mapping, single‑cell & spatial analysis, and cell segmentation in brain, tumor, and other tissues. Purpose
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exclusively on the spatial analysis of images, making them sensitive to optical aberrations, difficult to implement in depth, and inherently limited in the type of information they can extract. Our group
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams, Saelens
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on complex problems involving the development of new theories and methodologies. The research will be largely focused on the development of predictive computational tools for the analysis of the spatial spread
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communities • Multivariate statistical analysis of community and environmental datasets • Spatial analysis and georeferencing of ecological data using GIS • Development and implementation of species