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, land-use change, and environmental dynamics. • Design and implement spatial analytics and geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and
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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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turbines génératrices de courant). La limite en résolution spatiale du lidar vent cohérent est liée à la durée de l'impulsion laser utilisée. Cette dernière ne peut pas descendre en dessous de la centaine de
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to lead impactful research at the interface of aging biology, neurodegeneration, and spatial omics. The successful candidate will contribute to high-profile projects investigating the cellular and molecular
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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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research methods applied to urban contexts.• Experience with spatial modelling software (Metashape), geographic information systems (ArcGIS Pro), creative tools(Photoshop), and quantitative (SPSS) and
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and immune trafficking models. High-Resolution Imaging: Proficiency in spatially-resolved multiplexed imaging and confocal whole-mount tissue analysis. scRNA-seq: Experience designing 10x Genomics
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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develop open-source, surrogate models of land-atmosphere exchange, at various spatial resolutions and using various methodologies, to contribute to a better understanding of the carbon and climate impacts
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Design, develop, and implement advanced algorithms, models, and software tools for spatial data analysis, machine learning, and AI-driven geospatial applications Lead and collaborate on interdisciplinary