Assistant Research Scientist- Ecosystem Modeling

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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

• 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

Position Information

The Assistant Research Scientist will be responsible for assisting in the development and application of EPIC/APEX model-based soil carbon modeling frameworks for improving agroecosystem sustainability. This position will assist a team of ecosystem modeling scientists to perform process-based ecosystem models based research and develop decision support systems. This position will also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more efficient and reliable.

Responsibilities:

• Aid in the development and application of soil carbon modeling frameworks in APEX/EPIC models.

• Aid in the development of GHG modules in SWAT+/APEX/EPIC.

• Integrating ML/AI with Process based modeling to develop/optimize decision support systems.

• 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.

Required Qualifications:

• Ph.D. in Ecology, agronomy, Geology, Environmental Science/Engineering, Civil Engineering, or related disciplines with emphasis on soil carbon modeling or agroecosystem assessment.

• Some relevant professional experience.

• Demonstrated publication record in agronomic/soil carbon modeling and analysis.

• Interdisciplinary teamwork skills with researchers across different disciplines.

• Flexibility to perform work in a team or individually with supervision.

• Good communication, interpersonal skills, professionalism, and competency.

• Ability to multi-task and work cooperatively with others.

Preferred Qualifications:

• Knowledge of computer models on watershed assessment and/or flood management.

• Knowledge of programming or scripting languages such as Python, Fortran, R or others.

• Experience in remote sensing data analysis and geographic information system.

• Experience in machine learning motivated algorithms and quantitative data analysis.

• Strong writing and communication skills.

What You Need to Know

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

Why Work at Texas A&M AgriLife?

When you choose to work for Texas A&M AgriLife, 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 AgriLife offers a comprehensive benefit package including the following:

• 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

Applicant Instructions

Applications received by Texas A&M AgriLife 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 LinkedIn profile to prepopulate the online application.

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.