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Field
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to agriculture, soil, water, environment, or engineering Experience with GIS, R, Python, Matlab, and similar advanced software platforms is desirable Experience with data organization, data management, and data
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sensing, GIS, and spatial analysis. Demonstrate proficiency in Python or R programming language. Preferred candidates will be versed in recent literature on retention silviculture, early rotation treatments
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the last 5 years Experience in multivariate statistical procedures and basic modelling Data analysis and management programming experience in R or Python GIS experience Excellent written and oral
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: Strong interest in community engagement, data science, or social impact Experience with data analysis tools (e.g., Excel, R, Python, GIS, etc.) is a plus Excellent written and verbal communication skills
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University of California, San Francisco | San Francisco, California | United States | about 2 months ago
, or Python. Experience with data visualization tools such as Microsoft Power BI, familiarity with relational databases and electronic health record–derived data, and proficiency in project management
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teaching, learning, and research requirements. They are subject matter experts; they are skilled in research data management, collections, statistics, GIS, metadata, digital preservation, scholarly
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(R, Python, etc.), and working knowledge of data management protocols. Experience with exposome or environmental data, multiomics integration, and exposure-wide association studies (ExWAS) and GIS
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training and experience in statistical analysis, coding (e.g., R, Python or similar), and Geographic IT (e.g., GIS, spatial analysis and modeling). Ability to work both independently and collaboratively
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field preferred. •Experience with GIS-based programming (Python, Arcade), and application development experience in web/desktop environment (e.g., R, JavaScript, Python, CSS, and Tableau); and vector
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disadvantaged under county‑level payment rules. Your role will involve: Extracting and processing geospatial data from CDL, Sentinel‑2 L2A, NASS QuickStats, NLCD, and Kentucky GIS portals Computing vegetation