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program; supporting forestry and invasive species surveys, outreach, and education efforts; participating in formal and informal human dimensions surveys; and collecting and analyzing data to identify
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, or extreme weather impacts on health. Experience with quantitative datasets and applying statistical or analytical methods using software such as R, SAS, Python, Stata, or similar tools. Familiarity with
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, Computer Science, Systems Engineering, or a closely related field. A postgraduate is required to have earned their degree within 5 years of the appointment start date. A PhD is not required at the time of selection
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validate diagnostic methods using real-time PCR or novel diagnostic techniques Organize and present data for method evaluation and publication Analyze and present data, with the opportunity to publish
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factors that influence disease risk in native plants, cover crops, beneficial vegetation, and agricultural systems. Build technical skills in serological and molecular diagnostic methods for plant pathogen
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. The host institution application closes on Oct. 2, 2026, at 3:00 p.m. ET/12:00 p.m. (noon) PT. Late, incomplete, or non-formally submitted applications will not be considered or accepted. Applications can be
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genetic, genomic, and phenotypic datasets, to support research and crop improvement. Basic and applied research is also conducted within this project. You will use methods in computational biology to
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associated mechanisms. The primary focus of the fellowship is to gain experience in applying the scientific method to field trials and lab assays, collecting plant samples and data, and maintaining
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for Grain and Animal Health Research in Manhattan, KS. Our mission is to develop economical, effective, and ecologically sound methods for managing insect pests of grain and processed commodities, improve
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phenotyping methods to assess susceptibility and evaluate established or newly developed screening approaches. This also includes developing and evaluating preharvest and postharvest treatments aimed