In this exciting role, you will combine data synthesis, ecological theory, and numerical model development to explore the dynamics of California and western US ecosystems under a changing climate and fire regime. You will test and apply a vegetation demographic model that resolves fire effects on forest structure and composition, to explore feedbacks and interactions between fire behavior, vegetation dynamics, climate change, and management practices over both historical and future periods.
What You Will Do:
Application of the FATES-SPITFIRE model across site-level and regional domains.
Testing of model sensitivity to uncertainty in wildfire processes, plant traits, climate, disturbance history, hydrologic environment, and land management.
Statistical analyses of fire behavior and effects data, forest census and other vegetation data, and hydrological data, and comparison to model results.
Exploration of coupled changes to vegetation structure and fire behavior under alternate climate and management scenarios for both the historical and future periods.
Prepare and submit publications to peer-reviewed journals.
Share results in group meetings, seminars, etc.
What is Required:
Ph.D. in relevant field (e.g., fire ecology, climate science, ecology, ecosystem science, forestry, hydrology).
Proficient coding skills in, at a minimum, data analysis languages (Python, R, matlab, etc), and ideally, also in compiled languages such as Fortran.
Knowledge of and interest in wildfire, carbon cycle and ecological science concepts.
Experience with analysis of both observational and model-derived datasets.
Ability to understand and use state-of-the-art land-surface and vegetation demography models.
Evidence of ability to publish research results in peer-reviewed journals.
Ability and desire to work within an integrated, multi-institution team whose activities span from field research to Earth system model development.
Experience working with one of the following class of models: land surface models, terrestrial biosphere models, individual-based/gap models, hydrological models, ecosystem models, vegetation demographic models.
Prior research on wildfire.
For full consideration, please apply by November 10, 2020.
This is a full-time, 1 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 4 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
This position is represented by a union for collective bargaining purposes.
Salary will be predetermined based on postdoctoral step rates.
This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
Diversity, equity, and inclusion are core values at Berkeley Lab. Our excellence can only be fully realized by faculty, students, and staff who share our commitment to these values. Successful candidates for our faculty positions will demonstrate evidence of a commitment to advancing equity and inclusion.
Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action 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. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: “Equal Employment Opportunity is the Law.”
Lawrence Berkeley National Laboratory encourages applications from women, minorities, veterans, and other underrepresented groups presently considering scientific research careers.