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operations professionals, national forest system staff, state foresters in the region, and contractors. The emphasis of the project will be the analysis of past restoration treatments relevant
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techniques with high-resolution mass spectrometry for the analysis of phytochemicals. Hand-on experiences on growing agricultural products in controlled environmental agriculture (CEA) Analytical method
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visual cues, attractants, pheromones, and trap crops. The participant will study the impact of agronomic and cultural practices on the development, population dynamics, and distribution of cotton jassids
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and testing a novel automated field-based high throughput phenotyping system. You will also assist in conducting experimental design, data collection from field experiments, and data analysis. Research
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: Build reproducible workflows, functions, and R or Python packages; develop visualization tools and open-source applications; and share code through collaborative platforms such as GitHub. Scientific
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apply? Through active involvement in these projects, you will further develop your skills in data collection, analysis, and interpretation related to toxicants, resuscitative adjuncts, and biological
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forest restoration Develop skills in modeling silvicultural treatment outcomes Acquire advanced data analysis skills in the data management, analysis, and visualization of long-term experiments Detail
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of the relevant fields (e.g. Ecology, Forestry, Climatology, Geography). Degree must have been received within the past four years, or anticipated to be received by 9/30/2026. Preferred Skills: Data analysis and
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, data management, and analysis. Demonstrated experience in scientific writing and data analysis. Education and experience in data management, analysis, and visualization in R. Stipend $6,898.33 Monthly
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results of this study will be compared to NGS analysis of virus detection in a low complexity matrix. Overall, participation in the project will contribute to advancing the use of NGS for viral safety