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Postdoctoral Research Associate

Tamus

·

Today

Location
College Station, TX, United States of America
Type
Full-time
Department
Education
Seniority
Entry
Education
PhD
Source
Workday

Description

Job Title

Postdoctoral Research Associate

Agency

Texas A&M Agrilife Research

Department

Soil & Crop Sciences

Proposed Minimum Salary

Commensurate

Job Location

College Station, Texas

Job Type

Staff

Job Description

About Texas A&M AgriLife

Texas A&M AgriLife is comprised of the following Texas A&M University System members:

 

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 joining AgriLife!

 

Position Information

Job Summary:

We are seeking a Postdoctoral Research Associate position is responsible for coordinating and leading drone phenomics and quantitative genetics components of the corn breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep learning) and subsequent application to field studies and other phenomic data for biological discovery and breeding predictions.


Responsibilities:

-Under general supervision, is responsible for conducting research into phenomics quantitative genetics and maize breeding.

-Utilizes skills and knowledge in these and other areas to complete research projects leveraging new data extraction and analysis algorithms and connecting.

multidimensional data (phenomic, genomic, weather data) for biological discovery and prediction.

-Analyzes research data and summarizes results.

-Writes and contributes to research papers, articles, and publications and grants.

-Assists mentoring, and/or supervising student researchers and/or graduate students who are working on research related to the phenomics, quantitative genetics, and corn breeding program.

-Prepares presentation materials on research topic that may be presented to small and/or large groups.

-Actively participates in the preparation of required technical progress reports to research sponsors.

-Ensures program has sufficient and efficient computing capabilities (high performance research computing, workstations, software, network attached storage).

-Oversees drone activities (including drone equipment, data collection and supervision of student pilots, drone data storage and processing).

-Helps to coordinate research activities and success of graduate students, researchers, staff, and collaborators.

-Assists with corn breeding field work and leadership of research program as needed.

-Other duties as assigned.


Required Qualifications:

-Appropriate PhD in genetics, soil and crop sciences, computer science, remote sensing or related fields.

-Required experience in manuscript submission and publication.

-A drone license is required or to be obtained soon after hire.

-Excellent English verbal and written communication skills in presentations, writing, and email.

-Excellent knowledge, skills and abilities in drone data analysis, statistical analysis and AI (machine learning, deep learning).

-Ability to manage, organize, and back up large amounts of image and tabular data generated by program and collaborator labs.


Other Requirements:

-May have to work on the weekend and/or after normal hours.

-Travel is required to attend national meetings, meet with collaborators, and evaluate fields.

-Ability to work outside to plant, pollinate, harvest and process corn


Important Notice Regarding H1-B Sponsorship:

Your employment at Texas A&M AgriLife may require nonimmigrant sponsorship. A Presidential proclamation issued on September 19, 2025, imposes a $100,000 fee on new H-1B petitions filed after September 21, 2025. Texas A&M AgriLife will NOT pay this fee. If the fee is imposed on your petition, this offer of employment will be revoked. If actions taken during your employment result in the imposition of this fee, your employment will be terminated. To the extent that this statement conflicts with any applicable System or member Policy, Regulation, or Rule, this statement will control. We recommend that you consult with your private immigration counsel at your own expense regarding potential implications.

 

In addition, on January 27, 2026, Texas Governor Abbott issued a moratorium on the filing of any new H-1B unless approved by the Texas Workforce Commission. Accordingly, if you will now or in the future require sponsorship for employment visa status this moratorium may affect our ability to employ you should you be selected as the final candidate.

 

Benefits and Leave:

  • Health, dental, vision, life and long-term disability insurance (AgriLife contributes to premiums)
  • 12–15 annual paid holidays
  • Up to 8 hours/month sick leave and at least 8 hours/month vacation
  • Automatic enrollment in the Teacher Retirement System of Texas
  • Employee Wellness Initiative
  • Access to ongoing professional development and training through Aspire, LinkedIn Learning, and internally developed programs

How to Apply

Applications must include all job application data or a complete resume. Incomplete applications may be rejected. Applicants are encouraged to upload a resume or use LinkedIn to prepopulate application fields.


Required Documents:

Please attach to your completed application

Resume/CV

List of references with email and daytime phone numbers

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.

Skills

Machine LearningDeep Learning

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