Publisher
source

University of Georgia

Funded M.S. Research Assistantship in Forest Modeling and Quantitative Forestry at University of Georgia University of Georgia in United States

Degree Level

Master's

Field of study

Environmental Science

Funding

Funded M.S. Research Assistantship with a monthly stipend, tuition coverage, and partial student health insurance.

Deadline

Oct 20, 2026

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Country

United States

University

University of Georgia

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Keywords

Environmental Science
Agriculture
Biology
Natural Resource Management
Rainforest Ecology
Tropical Biology
Statistics
Programming Language

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About this position

Funded M.S. Research Assistantship in forest modeling and quantitative forestry at the University of Georgia’s Warnell School of Forestry and Natural Resources.

The project focuses on tropical forest growth and yield modeling, with strong connections to forest dynamics, FIA and long-term forest inventory data, climate and disturbance effects, statistics, and quantitative ecology. The work will use more than 20 years of forest measurements and includes collaboration with the USDA Forest Service FIA Program and the International Institute of Tropical Forestry.

This opportunity is a good fit for applicants interested in forestry, ecology, natural resource management, forest biometrics, forest modeling, and tropical forest ecology.

Funding includes a monthly stipend, tuition coverage, and partial student health insurance.

Applicants should have a bachelor’s degree in forestry, natural resources, ecology, environmental science, statistics, or a related field. Experience with statistics, data analysis, or programming is an advantage. International applicants may also need English-language examination documentation where applicable.

The deadline is October 20, 2026, and the expected start is Spring or Fall 2027.

Funding details

Funded M.S. Research Assistantship with a monthly stipend, tuition coverage, and partial student health insurance.

What's required

Applicants should have a bachelor’s degree in forestry, natural resources, ecology, environmental science, statistics, or a related field. Experience with statistics, data analysis, or programming is an advantage. International applicants may need to provide English-language examination documentation where applicable. Application materials include a CV, academic and research-interest statement, three professional references, unofficial transcript, and research publications or writing samples.

How to apply

Prepare the required application materials: CV, academic and research-interest statement, three professional references, unofficial transcript, and any research publications or writing samples. International applicants should check whether English-language exam documentation is needed. Submit by October 20, 2026.

More information can be found here

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