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Field
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quantitative discipline or equivalent experience. · Experience applying statistical or machine learning methods in real-world contexts. · Proficiency in Python and/or R for data analysis and modelling. · Strong
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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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: 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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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
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sustainability, environmental systems, and spatial data Skills in the following areas: Data analysis and programming, e.g. Python, R GIS and spatial analysis Data visualisation Language Requirements: Applicants
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, GIS/GeoAI, UAV applications, and resilient infrastructure planning. The candidate with experience translating cutting-edge research (e.g., AI) into operational decision-support systems for agencies and
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projects-tracking misinformation, analyzing climate change data, and building machine learning models-before advancing into GIS (Geographic Information Systems), network analysis, and responsible technology
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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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the following areas: Data analysis and programming, e.g. Python, R GIS and spatial analysis Data visualisation Language Requirements: Applicants must demonstrate at least B2-level proficiency in the language of