University of California-Berkeley
Associate/Full Specialist - Forest Carbon - MCECO - ESPM Ecosystem Sciences Divi
University of California-Berkeley, Berkeley, California, United States, 94709
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. The minimum full‑time base salary range for this position is $75,600–$154,200. Off‑scale salaries 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), within the Department of Environmental Science, Policy, & Management at the University of California, Berkeley, is seeking highly motivated individuals to apply for the position of Associate or Full Specialist. The Lab studies forest ecosystems in terms of ecology, management, and policy. Robust, quantitative analysis of forest and fuel inventory data is central to our approach. We collaborate with ecosystem scientists, remote sensing experts, and data scientists to develop scientifically robust and management‑relevant information that improves the health of California’s forests, reduces wildfire vulnerability, and supports natural climate solutions. One focal area is the carbon dynamics of forests in the era of global change. We track trends across the vast California forest landscape, using the Forest Inventory and Analysis (FIA) program, which currently intensifies its cycle to every five years under California Department of Forestry and Fire Protection (CalFire). The Lab collaborates with CalFire to utilize these intensified inventories for carbon flux and storage studies. Specific objectives include: Review and revise the current forest ecosystem carbon accounting framework used by CalFire. Develop statistically sound analytics that leverage time‑intensified FIA data to improve forest carbon accounting in California. Create analytical workflows using open‑source statistical computing platforms. 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 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:
The employment contract follows the standard UC Berkeley academic researcher agreement. 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 five years of research experience, or a Master’s degree or equivalent international degree plus three 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 its 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. 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. In searches when letters of reference are required, all letters will be treated as confidential per University of California policy and California state law. As a condition of employment, the finalist will be required to disclose if they are subject to any administrative or judicial decisions within the last seven years determining that they committed any misconduct. Job location
Berkeley, CA
#J-18808-Ljbffr
Position title:
Associate Specialist or Specialist Salary range:
The UC academic salary scales set the minimum pay determined by rank and step at appointment. The minimum full‑time base salary range for this position is $75,600–$154,200. Off‑scale salaries 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), within the Department of Environmental Science, Policy, & Management at the University of California, Berkeley, is seeking highly motivated individuals to apply for the position of Associate or Full Specialist. The Lab studies forest ecosystems in terms of ecology, management, and policy. Robust, quantitative analysis of forest and fuel inventory data is central to our approach. We collaborate with ecosystem scientists, remote sensing experts, and data scientists to develop scientifically robust and management‑relevant information that improves the health of California’s forests, reduces wildfire vulnerability, and supports natural climate solutions. One focal area is the carbon dynamics of forests in the era of global change. We track trends across the vast California forest landscape, using the Forest Inventory and Analysis (FIA) program, which currently intensifies its cycle to every five years under California Department of Forestry and Fire Protection (CalFire). The Lab collaborates with CalFire to utilize these intensified inventories for carbon flux and storage studies. Specific objectives include: Review and revise the current forest ecosystem carbon accounting framework used by CalFire. Develop statistically sound analytics that leverage time‑intensified FIA data to improve forest carbon accounting in California. Create analytical workflows using open‑source statistical computing platforms. 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 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:
The employment contract follows the standard UC Berkeley academic researcher agreement. 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 five years of research experience, or a Master’s degree or equivalent international degree plus three 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 its 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. 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. In searches when letters of reference are required, all letters will be treated as confidential per University of California policy and California state law. As a condition of employment, the finalist will be required to disclose if they are subject to any administrative or judicial decisions within the last seven years determining that they committed any misconduct. Job location
Berkeley, CA
#J-18808-Ljbffr