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USDA-ARS Internship in Software Engineering for Agricultural Genomic Data

ARS Office/Lab and Location: A research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Corn Insects & Crop Genetics Research Unit (CICGRU) located 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. 

Research Project: This project will involve applying software engineering and database best-practices to develop systems for storing, relating, and accessing genetic and genomic data for crop plants -- in particular, for soybean and related legume species. The internship will involve collaborating with a team of geneticists, computational biologists, and programmers, to develop and extend data storage systems and online interfaces for use by researchers and breeders. Computational tools developed by the group are used to identify the molecular basis for genetic loci that may be responsible for traits such as seed size and composition, plant architecture characteristics, disease and pest defense responses, and plant maturity and yield.

Learning Objectives: Throughout the appointment, the participant will have opportunity to learn the following: 1) methods for structuring and storing genetic and genomic data sets, and for assessing them in terms of content and format; 2) methods for robust software development, to produce modular, extensible, and maintainable software; 3) methods for genomic analysis, including for genomic sequence comparison, visualization, and evolutionary analysis; 4) methods for performing computational biology investigations in a Unix high-performance computing environment; and 5) methods for distributed code development and documentation. Particular software methods will include web services, a static site generator framework, databases and structured, indexed flat-files, the git distributed version control system, and Unix filesystem and computational environment.

Mentor(s): The mentor(s) for this opportunity is Steven Cannon ( If you have questions about the nature of the research project, please contact the mentor(s).

Anticipated Appointment Start Date: January 2, 2023. Start date is flexible and will depend on a variety of factors.

Appointment Length: 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: The hours per week are negotiable, depending on candidate needs - ranging between part time (20 hours per week) to full time (40 hours per week).

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience. 

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

ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and ARS. 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 in this program. Health insurance can be obtained through ORISE.

Questions: Please visit our Program Website. After reading, if you have additional questions about the application process please email and include the reference code for this opportunity.

The qualified candidate should be currently pursuing or have received a bachelor's degree in one of the relevant fields.

Preferred Skills:

  • Knowledge of methods for web front-end development, including Javascript, HTML, and CSS.
  • Knowledge of the Unix/Linux operating system and shell.
  • Knowledge of one or more scripting languages, e.g. Perl, Python, Ruby, or R.
  • Knowledge of software engineering methods, including code-cycle approaches such as Agile, and abstraction approaches such as web services and interface layers.
  • Desirable: experience with genomic data and bioinformatic methods.