Postdoctoral Research Scientist – Agroecosystem Modeling (SWAT) Apply for the Postdoctoral Research Scientist – Agroecosystem Modeling (SWAT) role at Texas A&M AgriLife Research. Job Details Agency: Texas A&M AgriLife Research Department: Temple Location: Temple, Texas Job Type: Staff (Full-time) Proposed Minimum Salary: Commensurate 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, and Texas A&M Veterinary Medical Diagnostic Laboratory. As the nation’s largest 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 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. Position Information The SWAT+ modeling group at Texas A&M AgriLife Research is seeking a highly skilled and motivated Postdoctoral Research Scientist to join a collaborative, high‑impact intercomparison project funded by the USDA and led by Columbia University. The successful candidate will be an integral part of a leading soil and water modeling team, focusing on advancing the science of biogeochemical process modeling—specifically related to carbon and nitrogen cycling (e.g., soil organic carbon and N 2 O fluxes) in U.S. agricultural lands. This is a two‑year position funded by grants, and availability is contingent on grant funding and satisfactory job performance. Responsibilities Model Execution & Analysis: Conduct detailed SWAT+ modeling activities at field, regional, and national scales, including scenario modeling and model scaling evaluation, following established protocols. Protocol and Data Contribution: Co‑develop model intercomparison and data sharing protocols, and contribute expert knowledge and datasets for model inputs, calibration, and validation. Documentation and Reporting: Meticulously document data processing, model structure, and modeling approaches. Deliver all modeling outputs on time. Model Advancement: Provide critical feedback, improvements, or recommendations for model advancement based on the intercomparison outcomes. Collaboration and Engagement: Actively participate in regular check‑in meetings, workshops, and engage with stakeholders. Scholarly Output: Collaborate on comprehensive analyses, presentations, and co‑author multiple high‑impact peer‑reviewed publications. Perform other duties as assigned. Required Qualifications A Ph.D. in Agricultural Engineering, Hydrology, Environmental Science, Soil Science, Computer Science, or a closely related field. Strong background in SWAT or SWAT+ model application, calibration, and validation. Strong scripting and/or programming skills in languages such as R, Python, and/or Fortran. Strong communication skills (written and verbal) and a proven ability to work effectively and professionally within a senior research team structure. Demonstrated strong problem‑solving skills and an ability to independently address complex research challenges. Ability to multitask and work cooperatively with others. Ability to work effectively within a structured research environment, including willingness to follow established protocols and directives from project leadership. Demonstrate professionalism, collegiality, and respect for team hierarchy while supporting the project's collaborative goals. Ability to maintain confidentiality and professionally manage sensitive data or information as required by project agreements. Ability to maintain flexibility and adapt to evolving project needs, priorities, and timelines. Demonstrated reliability in meeting deadlines and managing multiple tasks in a dynamic academic/research environment. Proficiency in working in an interdisciplinary, geographically distributed team. Preferred Qualifications Understanding of biogeochemical process modeling related to carbon and nitrogen cycling, including soil organic carbon and N 2 O fluxes, and their relation to soil fertility and nutrient use efficiency. Other Requirements Willingness and ability to occasionally travel for project meetings, workshops, and/or stakeholder engagement activities as required by the project. Commitment to uphold research integrity and comply with institutional, grant, and data management policies. Willingness to contribute to a positive and respectful work culture. What You Need To Know Salary: Compensation for this position is commensurate based on the selected candidate’s qualifications. Position Funding: This is a two‑year position funded by grants, and availability is contingent on grant funding and satisfactory job performance. Required Documents: CV/resume, cover letter, and list of references are required. Failure to provide all required documents could result in an invalid submission and a rejected application. Why Work at Texas A&M AgriLife? Working for Texas A&M AgriLife offers a comprehensive benefit package, including: 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. Equal Opportunity/Veterans/Disability Employer. 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. Seniority Level Internship Employment Type Full‑time Job Function Research, Analyst, and Information Technology Industries Research Services #J-18808-Ljbffr Texas A&M AgriLife Research
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