Graduate Student (MS or PhD) in Quantitative Ecology

Conservation Opportunity; Durham (NH); On-site; USD 28,000 - 35,000; Full time

Job summary

The Quantitative Marine Ecology Lab at the University of New Hampshire is seeking 1-2 motivated graduate students (MS or PhD) to begin in Fall 2026. Students will work with secondary datasets such as eBird and BioTime to study optimal designs for long-term ecological monitoring programs.

Salary includes a yearly stipend of $31,520, plus tuition and health insurance coverage. Applicants should have a strong background in data science or mathematical modeling and be prepared to expand skills in R

Qualifications

• Strong background in data science or mathematical modeling.
• Experience with or willingness to expand skills in: R programming and quantitative methods (statistics, mathematical modeling, decision science).
• Commitment to collaborative research in ecology.

Responsibilities

• Use secondary datasets (e.g., eBird, BioTime) to investigate questions about optimal design of long-term ecological monitoring programs.
• Collaborate with the lab to design, implement, and communicate research findings.

Skills

Data science background

Mathematical modeling

R programming

Education

MS or PhD candidate in a relevant field

Tools

R

Job description

Graduate Student (MS or PhD) in Quantitative Ecology

Graduate Student (MS or PhD) in Quantitative Ecology

Position: Graduate Student (MS or PhD) in Quantitative Ecology

Entity: Quantitative Marine Ecology Lab (Dr. Easton White), University of New Hampshire

Salary: Minimum yearly stipend of $31,520 (including summer; increases annually and higher if entering with an MS). Includes tuition and health insurance coverage.

Deadline: Priority deadline for Fall 2026 admission is January 15, 2026

Description:

“The Quantitative Marine Ecology Lab is seeking 1-2 motivated graduate students (MS or PhD) to begin in Fall 2026. Students will use secondary datasets (e.g., eBird, BioTime) to investigate questions about the optimal design of long-term ecological monitoring programs.

Requirements:

• Strong background in data science or mathematical modeling
• Experience with or willingness to expand skills in: R programming and Quantitative methods (statistics, mathematical modeling, decision science)
• Commitment to collaborative research in ecology
• Why you are specifically interested in joining Dr. White's lab
• Your relevant experience and research interests