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Field
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expertise in forest ecology, disturbance ecology, and landscape ecology, and methodological expertise in harmonizing distinct databases (e.g., forest inventory, remote sensing, land cover), GIS, and R-based
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learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with GIS software and Python, strong written
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proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team
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, Hydraulics, or related fields. Proficiency and experience in hydrologic and hydraulic modeling tools such as HEC-HMS, HEC-RAS, SWMM, InfoWorks, LISFLOOD, and SFINCS. Proficiency in GIS software (e.g., ESRI
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diverse soil and management conditions - Excellent technical knowledge of nitrogen dynamics and loss pathways in crop production - Proficiency in GIS and remote sensing workflows, using tools like QGIS, R
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within the past 3 years in Environmental Science, Geography, Computer Science, Atmospheric Sciences, or related field. Advanced GIS and geospatial computing expertise. Demonstrated commitment and ability
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modeling (regional planning, ecological, hydrologic climatic, or wildfire modeling). Experience with scientific software development in C/C++, FORTRAN and/or Python. Experience working with geo-spatial
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: Analyses Utilize statistical programming languages including but not limited Stata, SAS, R, Python. Perform data linkages. Perform statistical analysis of large dataset to investigate the associations
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MDBs/IFIs Strong publication record Experience working in participatory processes Experience in decision analysis and support processes Teaching experience Experience in geospatial modeling and GIS