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extraction methods Proficient in program R Proficient with spatial software (e.g., ArcGIS, R, QGIS) Proficient with Microsoft software Comfortable doing research in a remote location and in inclement weather
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applying models of insect movement, and develop predictive models. This research aims to collect movement data and produce models to enhance current surveillance, control, and eradication methods, such as
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distilling process that can be attributed to barley variety or processing methods. Summarized data will be disseminated to collaborating scientists located across the US. Learning Objectives: The fellows will
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-resistant weeds, supporting the development of sustainable agricultural practices. The successful candidate is expected to (1) help develop novel methods that incorporate advanced technologies for detecting
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state-of-the-art experimental and computational models for solving water resource problems worldwide. CHL research and development addresses water resource and navigation challenges in a variety of
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dairy production systems, soil ecology, forage production, forage quality, nutrient management, and ecosystem services. Research Project: The perennial grass breeding program at the USDFRC develops cool
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machine learning methods for disease quantification. Through the course of the project, they will gain in-depth knowledge of issues and the latest research at the junction of plant pathology and plant
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microbiological, molecular biological, and chemical methods. This includes characterizing fungal populations and quantifying aflatoxin concentrations, which are critical components of plant pathology research
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applying models of insect movement, and develop predictive models. This research aims to collect movement data and produce models to enhance current surveillance, control, and eradication methods, such as
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advanced methods to generate insight and reduce burden (Analytics and Artificial Intelligence). Creating trusted, ready-to-use data (Data Management). Equipping staff to work independently with data (Data