TES Research Assistant - Chen - Physiological Data Analyses

TES Research Assistant - Chen - Physiological Data Analyses Please see Special Instructions for more details.

Position Information

Requisition Number: TES
3254P

Home Org Name:
Forestry Wildlife and Environment

Division Name:
College of Forestry, Wildlife, and Environment

Position Title:

TES Research Assistant - Chen - Physiological Data Analyses

Estimated Hours Per Week: 40

Anticipated Length of Assignment: 4 months

Job Summary

The TES Research Associate will work with scientists and students under my supervision to support research related to AI-driven modeling of forestry systems, plant physiological processes, and ecological traits. The position will focus on developing computational models integrating multi-source datasets, including remote sensing, field measurements, environmental variables, and biological trait data.

Temporary Employment Services (TES) is an in-house support center established to meet the temporary employment needs of Auburn University. TES provides qualified and dedicated temporary employees in a wide variety of occupations to meet staffing needs throughout the campus. Temporary employees are hired for a variety of reasons with the most common being: assistance in the place of a regular employee who is absent for a specified period of time;

additional assistance during periods of abnormal or peak workloads; assistance with special projects; seasonal work.
AU student employees are not eligible for TES.

Essential Functions

• Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets.
• Modeling plant growth, carbon allocation, stress response (e.g., drought, salinity), and ecosystem productivity using AI-based approaches.
• Integrating multi-modal datasets (remote sensing, UAV/drone imagery, field inventory data, soil and climate parameters, and genomic/trait data).
• Conducting statistical modeling, feature selection, and predictive analytics for forest health, resilience, and biomass estimation.
• Supporting data preprocessing, cleaning, normalization, and database organization.
• Assisting in the preparation of research reports, manuscripts, and grant proposals.
• Providing hands‑on experience in applying artificial intelligence and computational modeling techniques to complex biological and ecological systems, with applications in forest productivity, climate resilience, and sustainable resource management.

Why Work at Auburn?

• Life‑Changing Impact
  :
  Our work changes lives through research, instruction, and outreach, making a lasting impact on our students, our communities, and the world.
• Culture of Excellence
  :
  We are committed to leveraging our strengths, resources, collaboration, and innovation as a top employer in higher education.
• We’re Here for You
  :
  Auburn offers generous benefits, educational opportunities, and a culture of support and work/life balance.
• Sweet Home Alabama
  :
  The Auburn/Opelika area offers southern charm, vibrant downtown scenes, top‑ranked schools, and easy access to Atlanta, Birmingham, and the Gulf of Mexico beaches.
• A Place for Everyone
  :
  Auburn is committed to fostering an environment where all faculty, staff, and students are welcomed, valued, respected, and engaged.

Ready to lead and shape the future of higher education? Apply today! War Eagle!

Minimum Qualifications

Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a closely related field.

Desired Qualifications

• Experience in machine learning, deep learning, and statistical modeling.
• Experience handling large‑scale ecological, biological, or remote sensing datasets.
• Strong scientific writing and communication skills.
• Interest in interdisciplinary research in forestry, plant physiology, and ecosystem science.

Salary Range

$20.00 per hour

Work Hours

City position is located in:
Auburn, Alabama

Posting Date: 02/11/2026

Equal Opportunity Compliance Statement

It is our policy to provide equal employment and education opportunities for all individuals without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, gender expression, pregnancy, age, disability, protected veteran status, genetic information, or any other classification protected by applicable law. Please visit our website to learn more.

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