Postdoctoral Scholar in Forest Ecology and Data Science

Position overview

Position title: Postdoctoral Scholar in Forest Ecology and Data Science Salary range: The posted UC system-wide salary scales set the minimum pay based on prior months of postdoctoral service (both domestic and international) before the start of appointment. See Table 23 for the experience level minimums for this position. Salary offers are determined based on qualifications and level of experience, budget, and the application of fair, equitable, and consistent pay practices at the University. The full salary range for this position is $69,073 to $82,836. Salaries that are higher than the published system-wide salary at the designated experience level minimum are offered when necessary to meet competitive conditions. Percent time: 100% Anticipated start: May 1, 2026 or later Position duration: Two years, with the potential for extension based on performance, length of research project and availability of funding.

Application Window

Open date: April 9, 2026

Most recent review date: Thursday, Apr 23, 2026 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Tuesday, Jun 30, 2026 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 Landscapes of Change (LOC) Lab at the Bren School of Environmental Science & Management invites applications for a postdoctoral researcher in forest ecology and data science. The successful candidate will join a dynamic, interdisciplinary group investigating how climate change is reshaping forests through shifting disturbance regimes. The position centers on data-driven research using large, multi-source datasets to understand how drought, fire, bark beetles, disease, and their interactions influence forest structure, function, and recovery.

We are especially interested in candidates with strong quantitative and computational skills, experience in big-data analysis, and a deep interest in forest disturbance dynamics. We welcome applicants who enjoy building reproducible, data-intensive workflows and contributing to a collaborative research culture that spans multiple disciplines and career stages.

Project/Position description:

-Harmonize field-based observations with remotely sensed datasets (e.g., Landsat, MODIS) across spatial and temporal scales.
-Quantify disturbance impacts and recovery trajectories, and develop rigorous modeling frameworks to test hypotheses about forest resilience and disturbance interactions.
-Collaborate across multiple disciplines, publish in leading journals, and present at major conferences.

School :

Qualifications

Basic qualifications (required at time of application)

Applicants must have completed all requirements for a PhD (or equivalent) in ecology, quantitative ecology, forest ecology, landscape ecology, or a related field, except the dissertation, at the time of application.

Additional qualifications (required at time of start)

Ph.D. in ecology, quantitative ecology, forest ecology, landscape ecology, or a related field. Ph.D. must be in awarded by the start of the position.

Preferred qualifications

-Publication record in relevant areas
-2-3 years of experience at the post-doctoral level
-Excellent quantitative and modeling skills including advanced coding in R and/or Python
-An interest and track record in publishing in top academic journals
-Familiarity with forest ecology and disturbance interactions
-Experience in big data analyses and developing reproducible workflows
-Proficiency using GitHub and coding languages, and other modern data management, sharing, and presentation interfaces
-Ability to work independently and collaboratively across disciplines
-Strong writing, communication, and organizational skills

Application Requirements

Document requirements

• Curriculum Vitae - Your most recently updated C.V.

• Cover Letter

• Sample Publication

Reference requirements

• 3-5 required (contact information only)

Only the finalists' references will be contacted.

Apply link:

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About UC Santa Barbara

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 for Employees, students and third parties
• APM - 035: Affirmative Action and Nondiscrimination in Employment

Additionally, you will be required to comply with the University of California Policy on Vaccination Programs, as may be amended or revised from time to time. Federal, state, or local public health directives may impose additional requirements.

The University of California 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, protected veteran status, or other protected status under state or federal law.

Job location

Santa Barbara, CA

Required

Preferred

Job Industries

• Other