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

University of California-Berkeley
United States, California, Berkeley
Oct 24, 2025
Position overview
Position title:
Associate Specialist or Specialist
Salary range:
The UC academic salary scales set the minimum pay determined by rank and step at appointment. See the following table(s) for the current salary scale(s) for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-july-2025-scales/t24-b.pdf. The current full-time base salary range for this position is $75,600-$154,200. "Off-scale" salaries, which yield compensation that is higher than the published system-wide salary at the designated rank and step, are offered when necessary to meet competitive conditions.
Percent time:
50%
Anticipated start:
Fall/Winter 2025
Position duration:
One year with the possibility of extension based on performance and availability of funding.


Application Window


Open date: October 24, 2025




Next review date: Saturday, Nov 8, 2025 at 11:59pm (Pacific Time)

Apply by this date to ensure full consideration by the committee.




Final date: Monday, Nov 24, 2025 at 11:59pm (Pacific Time)

Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.



Position description

The Forest Ecology Lab, under the guidance of Dr. John Battles (PI), with the Department of Environmental Science, Policy, & Management (ESPM) within the Rausser College of Natural Resources (RCNR) at the University of California, Berkeley, is seeking highly motivated individuals to apply for the position of Associate or Full Specialist.

The Forest Ecology Lab is a group of scholars who share an interest in understanding forest ecosystems in terms of their ecology, management, and policy. Robust, quantitative analysis of forest and fuel inventory data form the core of our approach. Specifically, we want to know how and why forests change. Answering these questions is more than just an interesting academic puzzle. We expand the scope of our field-based insights by collaborating with a diverse group of ecosystem scientists, remote sensing experts, and data scientists to develop scientifically robust and management relevant information. Specifically, we work with scientists, managers and policy makers in California to develop the best available information to improve the health of our forests, to reduce their vulnerability to high severity wildfire, and to ensure they continue to serve as cost-effective natural climate solutions.

A long-term, focal area for the Lab is understanding the carbon dynamics of forests in the era of global change. Given the increasing pace of unexpected and novel conditions, it has become more important than ever to measure changes in forest composition, structure, and function with high spatial and temporal fidelity. Moreover, we need to track trends across the vast and diverse forest landscape of California. The Forest Inventory and Analysis (FIA) program delivers current, consistent, and credible information about the status of forests and forest resources within the United States. In California, FIA repeats its inventory every ten years. Recently, the California Department of Forestry and Fire Protection (CalFire) has intensified the FIA cycle in California to every five years. The goal of this temporal intensification is to provide more frequent and more informative assessments on the status of CA forests.

The Forest Ecology Lab, as part of Berkeley Forests, is collaborating with CalFire to make full use of the intensified FIA forest inventories to measure and understand trends in carbon flux and storage in California's forests.

Specific objectives include:

1) Review and revise the current forest ecosystem carbon accounting framework used by CalFire.

2) Develop statistically sound analytics that take advantage of the time-intensified FIA data to improve forest carbon accounting in CA.

3) Develop analytical workflows using open-source statistical computing platforms.

4) Provide fully reproducible analytics and thoroughly documented code.

The duties of the position include:

* 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 to ensure understanding and engagement with domain experts.

* Contribute expertise to the environmental data science workgroup at UC Berkeley

The candidate must be eligible to work in the United States. The department is unable to sponsor a visa/work permit.

Contract: https://ucnet.universityofcalifornia.edu/resources/employment-policies-contracts/bargaining-units/academic-researchers/contract/


Qualifications
Basic qualifications (required at time of application)

Bachelor's Degree or equivalent international degree

Additional qualifications (required at time of start)

Bachelor's degree or equivalent international degree plus 5 years of research experience or Master's degree or equivalent international degree plus 3 years of research experience.

Preferred qualifications

* 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 expertise (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 GitHub.

* Experience working with databases of national forest inventories (e.g., FIA) or other large data sets that involve forest inventory data.

* Demonstrated capacity to publish peer-reviewed articles or non-peer reviewed reports with strong dependency on monitoring data.


Application Requirements
Document requirements
  • Curriculum Vitae - Your most recently updated C.V.


  • Cover Letter


Reference requirements
  • 3 required (contact information only)

Apply link:
https://aprecruit.berkeley.edu/JPF05192

Help contact: jbattles@berkeley.edu



About UC Berkeley

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, 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.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.



  • "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  • UC Sexual Violence and Sexual Harassment Policy
  • UC Anti-Discrimination Policy
  • APM - 035: Affirmative Action and Nondiscrimination in Employment


Job location
Berkeley, CA
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