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cutting-edge single-cell, spatial, in vitro, and surgical approaches in multiple model species and in human organoids to investigate the uterine endometrium and maternal-fetal interface, with the goal
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://www.uidaho.edu/science/academics/earth-spatial-sciences Position Qualifications Required Experience · Experience developing and applying advanced statistical analysis and modeling to address ecological
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imaging, spatial data analysis, and machine learning. One arm of the project will seek to engineer diverse quantitative features (e.g., adapting concepts and metrics from network science [5] to characterise
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of visual texts and will focus on the semiotic analysis of the design dimension,whether artistic,design-related,or architectural,with particular reference to the role of corporeality and spatiality and the
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high spatial and temporal resolution. The Research Fellow will design and implement advanced bioinformatics pipelines to interrogate stem cell biology using multi-omics approaches, including RNA
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ovarian cancer. The laboratory has about 18 members that study ovarian cancer biology. We use a variety of cutting-edge methods, including spatial proteomics, spatial metabolomics, 3D organotypic cultures
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research and applications of advanced spatial data analysis methods, data collection, and interpretation of remote sensing data, database system theory, mapping, spatial data distribution, development of new
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ecology. Familiarity with New Mexico Flora. Experience using ArcGIS Pro software and other spatial analysis software. Vegetation community mapping and classification. Experience in field ecological data
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 5 hours ago
; epidemiologic research in chronic diseases; cancer epidemiology; spatial, environmental, social, and/or genetic epidemiology; aging; cardiometabolic and cardiovascular outcomes; substance use; injury prevention
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. Tissue sectioning for advanced spatial transcriptomic analysis. Leading the analysis of single-cell and spatial transcriptomics data. Applying and developing the analysis framework for spatiotemporal