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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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tissue using genetic mouse models, functional screens, and single cell and spatial omics technologies. More details about the laboratory: https://www.ibt.cas.cz/en/research-laboratories/laboratory
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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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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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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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the occupational risks faced by inhabitants of the Roman Empire influenced their choice of preferred cults. The main methods used in the project include spatial analysis, predictive modelling, statistics, and the
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sequencing data and to integrate multi-omics data to study cancer development and progression (work experience with the analysis of genomics data such as spatial and single cell, methylation, ATAC-seq etc. TCR
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interdisciplinary research group dedicated to developing integrated approaches to geospatial systems analysis. Our team pushes the boundaries of how spatial data can be used to tackle today’s pressing environmental
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cover letter to: Jenny Hasija Administrative Specialist jenifer@med.umich.edu Focus area: Spatial biology quantitative analysis. The selected candidate will perform quantitative analysis of spatial
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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