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About the Opportunity Job Summary Conduct spatial analysis and statistical modeling to evaluate cannabis cultivation density patterns across tribal, private, and boundary lands. Develop refined
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“Bayesian Enhanced Tensor Factorization Embedding Structure (BETTER)”, and this PhD project specifically aims at developing a unified, scalable, and interpretable framework for tensor analysis. Specifically
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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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persistence in chronic infections (Salmonella, Pseudomonas, and Achromobacter) by integrating spatial modelling, single-cell transcriptomics, advanced imaging data, and machine learning approaches. The goal is
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composition, healing potential, and immune responses. In-depth analysis will be performed with the state of the art sequencing techniques - single cell approach combined with short and long-read sequencing
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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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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
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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
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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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Position Details Position Information Internal Posting? Posting Number SP005180P Position Title Research Associate I - Spatial Data Division/College College of Natural Resources Department Forest