Associate​/Specialist - Forest Carbon MCECO - ESPM Ecosystem Sciences Division - Battles Lab

Application Window

Open date: October 24, 2025

Review date: November 8, 2025 at 11:59pm (Pacific Time)

Final date: November 23, 2025 at 11:59pm (Pacific Time)

Position title: Associate Specialist or Specialist

Salary range: $75,600-$154,200

Percent time: 50%

Anticipated start: Fall/Winter 2025

Position duration: One year with possible extension

The Forest Ecology Lab is part of the Department of Environmental Science, Policy, & Management at the Rausser College of Natural Resources, University of California, Berkeley. The lab is led by Dr. John Battles (PI) and focuses on quantitative analysis of forest and fuel inventory data to understand how forests change and to provide management and policy relevant information for California.

Collaborations include remote sensing experts, data scientists, and policy makers to develop robust, reproducible analytics. One key focal area is carbon dynamics in forests in the era of global change, using the intensified Forest Inventory and Analysis (FIA) data that is now collected every five years in California.

In partnership with Cal Fire and the Berkeley Forests initiative, the lab uses FIA inventories to measure and understand trends in carbon flux and storage across California’s diverse forest landscape.

• Review and revise the current forest ecosystem carbon accounting framework used by Cal Fire.
• Develop statistically sound analytics that take advantage of the temporally intensified FIA data to improve forest carbon accounting in CA.
• Develop analytical workflows using open‑source statistical computing platforms.
• Provide fully reproducible analytics and thoroughly documented code.

• In consultation with the PI and Co‑Investigators, develop robust data analysis plans that leverage the temporally intensified FIA inventories using appropriate statistical methods.
• Evaluate empirical results in terms of their ability to produce management‑relevant information at the appropriate spatial and temporal scale.
• Interpret and communicate applied research insights in peer‑reviewed manuscripts, reports, and outreach material.
• Build open‑science workflows that can be shared among collaborators.
• Conduct all research and analyses following best practices in reproducible science.
• Communicate technical program details effectively to a diverse group of fire scientists, resource managers, and forest ecologists.
• Contribute expertise to the environmental data science workgroup at UC Berkeley.

Basic qualifications: Bachelor’s Degree or equivalent international degree.

• A master’s degree or equivalent international degree in a relevant discipline (e.g., fire science, forestry, ecology, natural resource management, data science, statistics).
• Five or more years of experience in a relevant domain (e.g., forest biometry, forest science, natural resource assessment).
• Experience with open‑source programming languages and software used in environmental data science, with a preference for R.
• Proficiency with standard methods of tracking, sharing, and updating code and methodology such as Git Hub.
• Experience with national forest inventory databases (e.g., FIA) or other large data sets involving forest inventory data.
• Demonstrated capacity to publish peer‑reviewed articles or strong non‑peer‑reviewed reports with a strong dependency on monitoring data.

Document requirements:

• Curriculum Vitae – most recent C.V.
• Cover Letter.

Reference requirements:

• Three references (contact information only).

Qualified individuals must be eligible to work in the United States. The department is not able to sponsor a visa or work permit.

Berkeley, CA.

UC Berkeley is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. UC Berkeley is committed to diversity, equity, inclusion, and belonging. Further information can be found in UC’s affirmative action policies.

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