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using Microsoft Excel and/or programming languages such as R, Python, or MATLAB, with an emphasis on hydrological, agronomic, or environmental datasets. Familiarity with evapotranspiration estimation
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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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Charles Henry Turner Post-doctoral Fellow, Department of Geography & GIS, College of Arts & Sciences
. Job Overview The Department of Geography and GIS at the University of Cincinnati, Ohio, seeks a fellow in geography, geospatial artificial intelligence (GeoAI), and spatial data science for its Charles
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Postdoctoral Scholar to conduct research for an NIH-NSF funded project on human health, movement, and infectious diseases. Successful applicants will have experience in: either spatial analysis using GIS
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. Willingness to undertake extensive field work. On a regular basis, field work might require you to stay and work for several-day periods on Pulau Ubin. Desirable Skills Experience with using GIS software (e.g
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, Python or related statistical software. GIS expertise is ideal. Application Process Please submit an online application and attach the following documents: Short statement of research interest. Complete CV
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with
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procedures used in spatial data analysis and vegetation dynamics modeling is required. The candidate should have extensive practical experience in the use of R and GIS. Demonstrated skills of Bayesian modeling
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of ecological, coastal, and geological research as well as perform analyses with Remote Sensing (optical and lidar), Geographic Information Systems (GIS), Python, R, and/or other programming languages or image
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computational modeling, geometric morphometrics, multivariate and Bayesian statistics, spatiotemporal and spatial modeling (including GIS), causal inference, machine learning, AI, and statistical software