Postdoctoral Research Associate
About The Position
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.
Requirements
- 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.
Nice To Haves
- 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.
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.
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Education Level
Ph.D. or professional degree
