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Field
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at the field, drone, and satellite scale. Big data analysis including processing and analyzing EMIT hyperspectral datacubes over large spatial domains such as the Colorado Plateau and even global. Presenting
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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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and established on-farm trials in Africa. Conduct spatial analysis to predict yield at scales. Contribute to the overarching goals of the research project team. Supervise master and doctoral student
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and clinical outcome through comprehensive tumor profiling. The project integrates spatial transcriptomics, long-read sequencing, DNA methylation analysis, and microbiome profiling to gain a deeper
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packages for data processing and simulation. Analyze high-throughput photon event data to extract spatial and temporal correlations. Collaborate with experimental staff on algorithm validation and feedback
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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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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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responsibilities for this role include: Initiating, planning, and overseeing research projects Leading the analysis of complex multiomics data, including single-cell and spatial omics, using R or Python; experience
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The Center for Policy Research on Energy and the Environment at Princeton University invites applications for a postdoctoral or more senior researcher to conduct spatial quantitative research
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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