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with process-based models, including APEX, SWAT, EPIC, DayCent, or DNDC. Proficiency in computer programming, including scripting in Python, Fortran, or other computing tools for data processing and
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Knowledge, Skills and Abilities: o Experience with geographic information system (GIS) software (e.g., ArcGIS, QGIS) and remotely sensed imagery. o Proficient in the use of R, Python, SAS, STATA, or other
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. Preferred qualifications Training in econometrics and quantitative methods in agriculture/food systems. Proficiency in R and/or Python (data wrangling, modeling, visualization). Familiarity with survey design
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others. Preferred Knowledge, Skills and Abilities: ●Knowledge of standard laboratory procedures for manure and mortality management and analysis. ●Proficiency in Python, R, or MATLAB for data analysis
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gas measurements, eddy covariance, or soil gas flux systems. - Experience managing and analyzing large datasets using programming languages such as R or Python. - Experience in outreach, stakeholder
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(e.g., R, SAS, Python, or similar). Equipment Used: standard research equipment such as light emitting diodes, data logger, environmental sensors, LI-COR gas exchange system, fluorometer. Part time
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. Experience with trait-based ecology, ecometric or functional-trait modeling, or macroecological analyses. Experience with R, Python, or equivalent programming languages for statistical and spatial analyses
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decision support systems. The candidate would also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more efficient and reliable
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geospatial datasets, and programming languages (either R or Python). The ideal candidate should have excellent academic record, authored/co-authored publications, contributed to significant scientific meetings
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, ArcGIS, QGIS). Strong data analysis skills using Python, R, or similar analytical tools. Excellent organizational and communication skills. Ability to multi-task and work cooperatively with others