Postdoctoral Research Associate
About The Position
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! Postdoctoral Research Associate in Agricultural, Animal, Rangeland, or Environmental Sciences Location: Texas A&M AgriLife Research, Temple, Texas Project: Enhancing APEX for simulating environmental and economic impacts of CAFO operations using the APEX model, funded by USDA-NRCS. Texas A&M AgriLife Research is seeking a highly motivated and innovative Postdoctoral Research Associate to support a USDA-funded project evaluating concentrated animal feeding operations (CAFOs) and manure management systems using the APEX agroecosystem model. The successful candidate will contribute to the enhancement, integration, and evaluation of model components for farm-scale carbon and nitrogen cycling across various livestock and manure management practices.
Requirements
- Ph.D. in Agricultural Sciences, Animal Science, Rangeland Management, Environmental Sciences, or a closely related discipline.
- Demonstrated record of peer-reviewed publications.
- Experience in designing, analyzing, and interpreting data from field studies.
- Strong project management and technical writing capabilities.
- Ability to work both independently and collaboratively.
- Strong organizational skills and ability to manage multiple tasks simultaneously.
- Ability to multi-task and work cooperatively with others.
Nice To Haves
- Proficient understanding of factors governing carbon and nitrogen cycling in farm-scale CAFO operations.
- Prior experience with process-based models such as EPIC, APEX, RUFAS, BCSM, GLEAM, or similar simulation frameworks.
- Proficiency in scientific programming (e.g., Python, Fortran) for data processing, model development, and computational analysis.
Responsibilities
- Conduct comprehensive literature reviews and gap analyses on regenerative animal production systems, manure management in CAFOs, and C–N cycling in soils, vegetation, manure, and livestock.
- Acquire, curate, and analyze field measurement datasets and associated environmental and economic information for model parameterization and validation.
- Develop or enhance model algorithms simulating carbon and nutrient budgets under varying manure housing and management practices using scientific programming languages.
- Implement newly developed modules and improvements into the APEX ecosystem simulation model.
- Assess agroecosystem C–N cycling dynamics influenced by concentrated ruminant‑livestock operations and changing environmental conditions.
- Evaluate and refine the performance of the enhanced model across various dairy systems and livestock/grazing management scenarios.
- Document model development processes and disseminate research findings through peer-reviewed publications and technical reports.
- Performs other duties as assigned.
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
