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USDA ARS Fellowship in Animal Disease Modeling

*Applications are reviewed on a rolling-basis.

ARS Office/Lab and Location: A research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS). This opportunity may be located at a USDA facility in Manhattan, Kansas, at Mississippi State University, Mississippi, or conducted remotely or in a hybrid arrangement. 

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. 

Research Project: The participant will be mentored by a collaborative research team from the ARS Foreign Animal Disease Research Unit (FADRU) located at the National Bio and Agro-Defense Facility (NBAF), the Arthropod-Borne Disease Research Unit (ABADRU), and the Geospatial and Environmental Epidemiology Research Unit (GEERU) to model the risk of highly pathogenic avian influenza (HPAI) airborne transmission between U.S. poultry facilities. The primary focus of this opportunity will be on developing statistical and mathematical models to assess airborne transmission pathways and inform surveillance and control strategies. Secondary opportunities will be available to participate on projects on foot-and-mouth disease (FMD), African swine fever (ASF), vesicular stomatitis (VS), bluetongue (BT), epizootic hemorrhagic disease (EHD), and New World screwworm (NWS).  

This fellowship provides engagement with research in animal disease ecology, epidemiology, and quantitative modeling. The fellow will collaborate with an interdisciplinary team with expertise spanning disease modeling, statistics, epidemiology, genetics, and livestock systems. The fellow will also have the opportunity to collaborate with federal scientists, university partners at Mississippi State University, and the poultry industry to improve preparedness and response. Peer-reviewed publication of research findings will be encouraged and supported. 

Learning Objectives: The fellow will have the opportunity to gain or expand skillsets over a range of computational techniques needed for modern agricultural research and data analyses, including: 

  1. Model Development: Design and implement advanced statistical and mathematical models to support disease surveillance and risk assessment. 
  2. Software/Code Development: Build reproducible workflows, functions, and R or Python packages; develop visualization tools and open-source applications; and share code through collaborative platforms such as GitHub.  
  3. Scientific Communication: Produce reproducible analyses, publish findings in peer-reviewed journals, and present results at scientific conferences and stakeholder meetings. 
  4. Collaboration and Communication: Collaborate effectively within interdisciplinary teams and engage with researchers, veterinarians, and industry stakeholders to address complex questions in animal disease management.

Mentor(s): The mentors for this opportunity are John Humphreys (john.humphreys@usda.gov) and Amy Hudson (amy.hudson@usda.gov). If you have questions about the nature of the research, please contact the mentors.

Anticipated Appointment Start Date: 2025. 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 appointment is full time.

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience. The anticipated stipend range is $62,107 - $74,361 annually.

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 ORISE.ARS.Plains@orau.org and include the reference code for this opportunity.

Qualifications

 

The qualified candidate should be currently pursuing or have received a doctoral degree in the one of the relevant fields. Degree must have been received within the past five years or anticipated to be received by or near the start of appointment.

Preferred skills:

  • Proficiency in using at least one common programming language (e.g., R, Python, etc.). 
  • Demonstrated skills in developing statistical approaches for analyzing spatial and temporal data.  
  • Proficiency in processing and analyzing meteorological data. 
  • Knowledge of code and software development workflows and use of GitHub for managing code. 
  • Knowledge of the poultry industry or HPAI. 
  • Knowledge of disease ecology, epidemiological analysis, or disease modeling. 
  • Ability to effectively collaborate and perform with others. 
  • Demonstrated strong oral and written communication skills. 

Stipend

 

$62,107.00 – $74,361.00 Yearly

Point of Contact

 

Janeen

Eligibility Requirements

 

  • Citizenship: U.S. Citizen Only
  • Degree: Doctoral Degree received within the last 60 months or currently pursuing.