TES Research Associate
About The Position
The TES Research Associate will work with scientists and students under the supervision of Dr. Chen 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), a unit of the Auburn University Department of Human Resources, is an in-house support center established to meet the temporary employment needs of the university. TES provides qualified and dedicated temporary employees in a wide variety of occupations to meet the 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, Emergencies. If you are looking for an employment opportunity, TES is a great way to showcase your professional skills and assist Auburn University while gaining valuable work experience within higher education. AU students are not eligible for TES. This position will provide 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.
Requirements
- Master's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field.
Responsibilities
- 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
Benefits
- generous benefits
- educational opportunities
- a culture of support and work/life balance
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What This Job Offers
Career Level
Mid Level
