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USDA-ARS Postdoctoral Research in Plant Genetics

Job in Corvallis, Benton County, Oregon, 97333, USA
Listing for: ORISE
Full Time position
Listed on 2026-06-18
Job specializations:
  • Research/Development
    Research Scientist, Genetics / Genomics, Biology, Agriculture / Farming
  • Science
    Research Scientist, Genetics / Genomics, Biology, Agriculture / Farming
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Overview

A research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), located in Corvallis, Oregon. ARS is the USDA’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 delivers cutting‑edge, scientific tools and innovative solutions for 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.

Research

Project

The project seeks to develop molecular resources to advance breeding efforts for resistance to powdery mildew in hop (Humulus lupulus L.). The fellow will analyze readily available phenotypic and genotypic datasets from populations segregating for disease resistance. One population is a large, structured multi‑parent population, and another is a bi‑parental population. The fellow will develop a consensus genetic map, identify marker‑trait associations, determine the effectiveness of various methods to collect phenotypic data, conduct marker validation (also using existing datasets), and write publications for submission to peer‑reviewed journals.

The participant will build upon existing genomics and genetics data analysis skills to troubleshoot a complex dataset in an obligately out crossing, highly heterozygous species.

Learning Objectives
  • Develop molecular resources that support breeding for powdery mildew resistance in hop (Humulus lupulus L.).
  • Analyze complex phenotypic and genotypic datasets from multi‑parent and bi‑parental populations segregating for disease resistance.
  • Construct consensus genetic maps integrating data from structured and biparental populations.
  • Identify marker‑trait associations linked to powdery mildew resistance using appropriate statistical and genomic approaches.
  • Evaluate and compare phenotyping methods for their effectiveness in detecting reliable marker‑trait associations.
  • Conduct marker validation using existing datasets to confirm robustness and applicability in breeding programs.
  • Troubleshoot and analyze complex genomic datasets in an obligately out crossing, highly heterozygous species.
  • Communicate research findings through preparation and submission of manuscripts to peer‑reviewed scientific journals.

Mentor:
Kayla Altendorf (kayla.altendorf).

Appointments and Compensation

Anticipated Appointment

Start Date:

Summer 2026 (flexible). The appointment will initially be for one year, but may be renewed upon recommendation of ARS and is contingent on the availability of funds. Level of Participation:
Full time. Participant Stipend: A monthly stipend commensurate with educational level and experience, anticipated to range from $6,705.42 to $7,152.50.

Eligibility

Citizenship Requirements:
This opportunity is available to U.S. citizens only.

Qualifications

The qualified candidate should be currently pursuing or have received a doctoral degree in one of the relevant fields (e.g., plant breeding, genetics, applied plant science, plant biology, plant pathology, biostatistics, bioinformatics, genomics, or a related field).

  • Experience with managing large‑scale genomic and phenotypic datasets.
  • Preparing figures and manuscripts for peer‑reviewed publications or theses/dissertations.
  • Experience with common genomics and genetics programs.
  • Programming in R, Python, or similar.
  • Basic experience with computer programs such as Microsoft.
  • Experience with genetic data from out crossing, highly heterozygous species, or constructing genetic maps.
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