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development Required Qualifications Ph.D. in Bioinformatics, Computational Biology, Systems Biology, or a related field Proven experience in the analysis of single-cell or spatial omics datasets Strong
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, dynamic mapping, mobile application development, spatial data analysis, visualization, and GIS. The Lab conducts interdisciplinary collaborative projects with research partners on campus at the UO, with
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, focusing on atherosclerotic plaque samples collected from local hospitals in the region. Your primary responsibility will be to develop smooth muscle cell-based assays guided by single-cell spatial
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hydrology and social geography. Proficient in geographic information systems (GIS) and spatial data analysis. Experience in workshops organisation Good French speaking and reading capacities and good English
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join our dynamic research team. Our work focuses on craniofacial regeneration and distraction osteogenesis, using cutting-edge multi-omic approaches (single-cell and spatial transcriptomics, genetic and
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Cartographic Heritage to model the impact of land changes on the hydrological and river systems in Europe The main goal of this proposal is to develop strong research and analysis skills of a PhD student
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through model forests. Granular Matter, 22(1), 1–10. https://doi.org/10.1007/s10035-019-0980-9 Zhang, Y., Shen, C., Zhou, S., & Luo, X. (2022). Analysis of the Influence of Forests on Landslides in
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, College of Department: Data Science Rank: Associate Professor Annual Basis: 9 Month Application Deadline October 31, 2025 Required Application Materials Candidates are asked to apply online at https
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understanding and experience of cancer biology, cell and molecular biology, and biochemistry. Practical experience with bioinformatics and omics data (transcriptomics, proteomics, spatial data) and analysis (e.g
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environment collecting or analyzing data. Experience using GIS software to manipulate data and generate spatial data products (e.g., maps, web/story maps, etc.). Experience working with groups of stakeholders