USDA-ARS Postdoctoral Research Computational Biology Fellowship
Listed on 2026-07-08
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Research/Development
Research Scientist
Organization
U.S. Department of Agriculture (USDA)
Reference CodeUSDA-ARS-MWA-
Final date to receive applications8/28/2026 3:00:00 PM Eastern Time Zone
DescriptionApplications are reviewed on a rolling basis.
ARS Office/Lab and LocationA research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), National Animal Disease Center (NADC), Virus and Prion Research Unit (VPRU) in Ames, Iowa.
The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief scientific in‑house research agency with a mission to find solutions to agricultural problems that affect Americans every day from field to table. ARS will deliver cutting‑edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well‑being of all people; sustain our nation’s agroecosystems and natural resources;
and ensure the economic competitiveness and excellence of our agriculture. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence.
National Animal Disease Center (NADC) is the premier research institute within the U.S. Department of Agriculture (USDA) for studying diseases of large animals, and is located in Ames Iowa. At the NADC, scientists investigate microbe‑host interactions from every perspective—molecular, microbe, and natural host.
Research ProjectResearch will focus on the swine bacterial pathogens Streptococcus suis and Glaesserella parasuis, both of which are major contributors to high‑priority disease challenges and drivers of antibiotic use in swine production. The goal is to identify genetic and regulatory factors that influence disease outcomes in S. suis and G. parasuis. These insights are important for distinguishing virulent from non‑virulent strains and for supporting vaccine development.
The fellow will collaborate closely with microbiologists and immunologists to unravel the complex molecular mechanisms underlying host–pathogen interactions, including bacterial colonization of the respiratory tract and evasion of host immune defenses. This will be through analytical pipelines and developing algorithms for RNA‑seq and whole‑genome data.
Under the guidance of mentors, the fellow will learn to: (a) conduct research using swine infection models; and (b) utilize genomic and transcriptomic data to build comprehensive knowledge bases on the genetic factors influencing bacterial colonization and disease outcomes such as pneumonia, septicemia, meningitis, endocarditis, and polyarthritis.
Mentors- Tracy Nicholson – Tracy.
Nicholson - Samantha Hau – Samantha.
Hau
Start Date:
Flexible, anticipated 2026.
Length:
Initially one year, may be renewed upon recommendation of ARS and contingent on availability of funds.
Level of Participation:
Full time.
The participant will receive a monthly stipend commensurate with educational level and experience. Anticipated annual stipend is $75,284.
Citizenship RequirementU.S. citizen only.
ORISE InformationThis program is administered by ORAU. Participants do not become employees of USDA, ARS, DOE or the program administrator, and there are no employment‑related benefits. Proof of health insurance is required for participation. Health insurance can be obtained through ORISE.
QualificationsThe qualified candidate should be currently pursuing or have received a doctoral degree in one of the following fields: bioinformatics, computational biology, molecular biology, genetics/genomics, systems biology, microbiology, biostatistics, computer science. The degree must have been received within the past five years, or be anticipated to be received by 10/30/2026.
Preferred Skills- Understanding of bacterial genetics, disease biology, modern genomic and transcriptomic methods, such as comparative genomics, RNA‑seq, genome assembly, and other high‑throughput sequencing approaches.
- Familiarity with transcriptomic analysis packages (e.g., DESeq2, scanpy) and workflow managers (e.g., Nextflow, Snakemake).
- Prior use of bioinformatics tools, pipelines, and statistical methods…
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