Job Title: Postdoctoral Research Associate
Agency: Texas A&M Agrilife Research
Proposed Minimum Salary: Commensurate
Job Location: Temple, Texas
Job Type: Staff
– Aid in the development and application of a national scale modeling framework to support the Conservation Effects and Assessment Program. Prepare and process large datasets for use in national model assessments conducted with SWAT+.
– Aid in the development of software and tools to support large- and small-scale modeling efforts.
– Perform SWAT+ model input preparation using machine learning, remote sensing, and other techniques.
– Perform original research using hydrologic models at various spatial scales.
– Present research at workshops, conferences, and meetings. Document research in reports and peer reviewed publications.
– Work effectively within a modeling group comprised of ARS, AgriLife, and other personnel. Actively participate in joint research activities. Effectively manage and complete assigned tasks.
– Other job-related duties as required.
Education and Experience:
Candidate must hold a Ph.D. in Ecology, Hydrology, Geology, Environmental Science/Engineering, Civil Engineering, or related disciplines with emphasis on surface hydrology or watershed assessment. A successful candidate is expected to have demonstrated publication record in hydrological or water quality modeling and analysis and has interdisciplinary teamwork skills with researchers across different disciplines.
Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.
Preferred Knowledge, Skills and Abilities:
- Knowledge of computer models on watershed assessment.
- Knowledge of programming or scripting languages such as Python, Fortran, R or other.
- Experience in remote sensing data analysis and geographic information system
- Experience in machine learning motivated algorithms and quantitative data analysis
- Good interpersonal skills, professionalism, and competency
- Strong writing and communicating skills.
- Ability to multi-task and work cooperatively with others. Flexibility to perform work remotely, in a team or individually with supervision.
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/Affirmative Action/Veterans/Disability Employer committed to diversity.