Postdoctoral Research Associate

Postdoctoral Research Associate

Texas A&M Agri Life 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.

Location:

Texas A&M Agri Life Research, Temple, Texas

Project:
Enhancing APEX for simulating environmental and economic impacts of CAFO operations using the APEX model, funded by USDA-NRCS.

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.

Required Qualifications:

• 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.

Preferred Qualifications:

• 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.

Salary:
Compensation for this position is commensurate based on the selected candidate's qualifications.

Position Funding:
This position is contingents on performance and availability of funding. Continuation of the position is contingent upon ongoing funding.

Applicant Instructions:
Applications received by Texas A&M Agri Life 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 Linked In profile to prepopulate the online application.

Required Documents: CV/ resume, cover letter, list of references, and certifications/ additional documentation, if applicable.

Why Work at Texas A&M Agri Life?

When you choose to work for Texas A&M Agri Life, 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 Agri Life offers a comprehensive benefit package including:

• Health, dental, vision, life and long-term disability insurance with Texas A&M Agri Life 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 Agri Life

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.