Postdoctoral Research Associate

Job Title

Postdoctoral Research Associate

Agency

Texas A&M Agrilife Research

Department

Animal Science

Proposed Minimum Salary

$16.00 hourly

Job Location

College Station, Texas

Job Type

Staff

Job Description

About Texas A&M AgriLife

Texas A&M AgriLife is comprised of the following Texas A&M University System members:

• Texas A&M AgriLife Extension Service
• Texas A&M AgriLife Research
• College of Agriculture and Life Sciences at Texas A&M University
• Texas A&M Forest Service
• Texas A&M Veterinary Medical Diagnostic Laboratory

As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together a college and four state agencies focused on agriculture and life sciences within The Texas A&M University System. With over 5,000 employees and a presence in every county across the state, Texas A&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service.

Click here to learn more about how you can be a part of AgriLife and make a difference in the world!

Position Information

Texas A&M AgriLife Research seeks a highly motivated Post‑Doctoral Research Associate to join a multidisciplinary team developing advanced techno‑economic, systems modeling and decision‑support tools to improve the resilience of small and mid-sized dairy farms in the United States. The position is part of a USDA-funded project led by Dr. Sushil Paudyal and Dr. Karun Kaniyamattam, with close collaboration from a new PhD student and an extended multi-institutional research team across Texas, California, and Wisconsin.

This objective includes:

• Building conceptual causal loop diagrams (CLDs) to represent farm-level feedback structures.

• Developing and calibrating a quantitative system dynamics (SD) model to simulate alternative dairy management strategies under diverse economic and biological scenarios.

• Integrating outputs from dairy business analysis (DBA) and multi-criteria decision analysis (MCDA).

• Contributing to the development of an R Shiny–based, web-enabled decision-support tool for farmers, using machine learning (random forest) predictive models.

• Working closely with the PhD student and PIs to ensure rigorous model development, documentation, and validation.

This position offers unique opportunities to contribute to high‑impact translational research at the intersection of animal science, economics, systems modeling, data science, and agricultural decision-making.

Key Responsibilities

• Lead the design of system dynamics models for dairy farm decision-making, including development of stocks, flows, feedback loops, and scenario experiments.

• Translate conceptual CLDs into quantifiable models using software such as Stella Architect®, Vensim®, or similar SD tools.

• Integrate production, financial, and behavioral data collected in Objectives 1 and 2 into dynamic modeling structures.

• Conduct scenario analyses to evaluate management transitions (automation, organic transition, raw milk sales, dairy‑beef diversification).

• Collaborate on building a web‑based decision-support tool in R Shiny with ML-based predictive components.

• Mentor and work closely with a PhD student on model development and documentation.

• Prepare manuscripts for peer-reviewed journals and present findings at scientific conferences.

• Contribute to team meetings, stakeholder engagement, and project reporting.

Qualifications

Required:

• Ph.D. in Animal Science, Veterinary Medicine, Systems Science, Industrial Engineering, Applied Mathematics, Data Science, or a closely related field.

• Experience with system dynamics modeling (Stella, Vensim, Powersim, or similar).

• Strong quantitative and analytical skills, including programming in R, Python, or MATLAB.

• Excellent communication skills and demonstrated leadership ability to work within multidisciplinary teams.

• Peer-reviewed publications, strong knowledge of dairy systems decision-making

• Proven grantsmanship.

• Background in livestock systems, dairy science, or agricultural production economics.

Preferred:

• Experience with R Shiny app development, machine learning (e.g., random forests), or hybrid modeling frameworks.

• Familiarity with MCDA, CLDs, or agricultural decision-support tools.

• An interest in working directly with agricultural stakeholders and applied research.

Work Environment

This position is housed in the Department of Animal Science at Texas A&M University (College Station, TX). The postdoc will work closely with:

• Dr. Karun Kaniyamattam (AI-driven livestock systems modeling; system dynamics; dairy & beef economics)

Why Work at Texas A&M AgriLife?

When you choose to work for Texas A&M AgriLife, you become part of an organization that is an established leader in agriculture and life sciences with a wide range of capabilities to meet the needs of our statewide, national, and international constituents.

In addition, Texas A&M AgriLife offers a comprehensive benefit package including the following:

• Health, dental, vision, life and long-term disability insurance with Texas A&M AgriLife contributing to employee health and basic life premiums
• 12-15 days of annual paid holidays
• Up to eight hours of paid sick leave and at least eight hours of paid vacation each month
• Automatic enrollment in the Teacher Retirement System of Texas
• Employee Wellness Initiative for Texas A&M AgriLife

Applicant Instructions

Applications received by Texas A&M AgriLife must either have all job application data entered or a resume attached. Failure to provide all job application data or a complete resume could result in an invalid submission and a rejected application. We encourage all applicants to upload a resume or use a LinkedIn profile to prepopulate the online application.

Required Documents

CV/ Resume

Cover letter

List of references

Certifications/ additional documentation

May 15, 2026 hire date

All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.

Equal Opportunity/Veterans/Disability Employer.