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. This project contributes to Infectious Disease Pathology Brach (IDPB)’s molecular pathology program by applying molecular and sequencing-based methods to detect a broad range of pathogens in fixed tissues. Under
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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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, 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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will support genome-wide prediction of variant effects across pathogen populations represented in USDA-ARS culture collections. Simultaneously, protein language models and structural methods will
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, and environmental factors associated with diabetes incidence, prevalence, complications, and trends. Learn and apply advanced statistical and machine learning methods, including cluster analysis and
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environmental factors associated with CKD incidence and trends. Apply advanced statistical and machine learning methods, including semi-supervised cluster analysis, to characterize populations with diabetes and
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aerial vehicle (UAV) imagery collection and processing, deep learning methods, and rangeland vegetation communities in Oregon and Idaho as part of an interdisciplinary team including researchers in plant
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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