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Field
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LiDAR and UAV photogrammetry) with physiological and spectral indicators of forest health. The research will be conducted at multiple spatial scales, from single trees to landscapes, and integrated
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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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the start of the appointment and no more than four total years of postdoctoral experience. Proficiency in spatial analysis, with working knowledge of GIS concepts and tools (e.g., spatial data structures
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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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for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial and functional interactions within urban infrastructure. Personal and Organizational Skills Ability to model
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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storage potential and future carbon removal and carbon farming policy scenarios. It integrates process-based knowledge with machine learning and especially aims to spatially quantify uncertainties. You will
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, signal processing, wireless/optical communications, and communication system engineering Extensive experience in physical layer algorithm design and performance analysis Proven track record of publications
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academic qualifications at the PhD level in bioinformatics, computational biology, biomedical sciences or a related field. Documented expertise in scRNA-seq analysis and familiarity with spatial
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. Position Responsibilities: Develop and implement computational and systems biology approaches for network and hidden driver analysis from spatial omics and single-cell omics data. Collaborate with