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simulations to identify key mechanistic drivers of viral persistence and immune response, and use SciML to automatically select ODE/PDE models that include these mechanisms. The postdoc will develop
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molecular mechanisms driving lymphoma progression and therapy resistance. This position will leverage cutting-edge approaches including spatial transcriptomics, CRISPR-based functional genomic screening, and
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to the study of online harms. Ongoing projects in which these postdocs will be involved include – assessment of influence campaigns and measuring their impact, meme analysis, online threat detection, assessment
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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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control) due to multiple interacting disturbances such as wildfires, drought, and insect outbreaks. The researcher will apply and adapt a spatially explicit multi-hazard risk assessment framework developed
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The successful candidate will be responsible for developing computational and systems biology approaches to analyze spatial omics data and single-cell omics data (e.g., scRNA-seq, scATAC-seq, single
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of biotic heterogeneity in urban environments and the spatial/temporal dynamics of these drivers. This will involve working with pre-existing data collected by the lab, as well as collaborator data and
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-culture system to study disease. By integrating single-cell multiomics, spatial transcriptomics, long-read sequencing, and high-throughput functional imaging, we aim to identify disease-relevant phenotypes
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analysis pipeline for the resulting videos, and writing manuscripts. Additionally, this postdoc will work closely with a collaborative team of disease ecologists, movement ecologists, and veterinarians
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of biotic heterogeneity in urban environments and the spatial/temporal dynamics of these drivers. This will involve working with pre-existing data collected by the lab, as well as collaborator data and