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SWAT+gwflow Proven experience in modelling natural and human-induced drought (streamflow and groundwater drought). Proficiency in programming (R, Python, or MATLAB) and GIS tools. Experience in climate
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: Position 1: Postdoctoral Associate – Software Engineering & Technical Development Proficiency in Python, geospatial libraries, API design (e.g., FastAPI), and cloud/HPC environments. Experience with
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Information Science (GIS), and computational science for health and environment, to study processes spanning from the microscopic to the planetary, across all time scales. The Inverse Modelling group at the Department
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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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programming skills (e.g., Python, Ruby, PowerShell). A good working knowledge of Artificial Intelligence (AI) principles. Including LLMs and the use of AI Agents Experience working with GIS systems and
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integration, database systems, or data quality. 2. Skills: Proficiency in Python (data processing, APIs) and good engineering practices (Git, testing, documentation). Experience with at least one: vector search
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, Environmental Science, Agronomy, Plant Science, Soil Science, Agricultural Engineering, or related quantitative field. • Demonstrated experience in GIS-based spatial analysis. • Experience with quantitative
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Required Qualifications PhD in Animal Science, Environmental Science, Agronomy, Plant Science, Soil Science, Agricultural Engineering, or related quantitative field. Demonstrated experience in GIS-based
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with data analysis/modelling and programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication
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phosphorus-driven eutrophication, with experience in soil monitoring and erosion processes. Skills in GIS, spatial analysis of large scale data, modelling, remote sensing, and programming (R or Python