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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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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 13 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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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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ssantagata@bwh.harvard.edu Salary Range Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines Minimum
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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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computational social choice; please visit https://algo.win.tue.nl/ for more details on the cluster. The cluster provides a lively and international environment for your research. As a PhD student, you do need
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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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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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important jeu de données préliminaires (scRNA-seq de >120 000 cellules, transcriptomique spatiale, cytométrie spectrale), le projet s'articule autour de trois objectifs principaux : 1-Caractériser la
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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