NGEE-Arctic Vegetation Modeling Postdoctoral Scholar

Berkeley Lab’s Climate & Ecosystems Division has an opening for a NGEE-Arctic Vegetation Modeling Postdoctoral Scholar.


Date posted

Jan. 10, 2020 12:00 am

Application deadline

Mar. 10, 2020 12:00 am


Berkeley Lab’s Climate & Ecosystems Division


  • United States

Job description

Berkeley Lab’s Climate & Ecosystems Division has an opening for a NGEE-Arctic Vegetation Modeling Postdoctoral Scholar. We seek a postdoctoral scholar to model the impact of climate and disturbance on Arctic shrub distributions and feedbacks to climate change. You will be part of a team at Berkeley Lab working on the NGEE-Arctic project. This project aims to improve predictive understanding of the carbon-rich Arctic system processes and feedbacks to climate. The research goals for you are to project changes in arctic shrub distributions and future shrub expansion in response to climate change and to explore the controls and consequences of these vegetation shifts. The specific objectives for you will include developing representations of dynamic Arctic vegetation for a demographic, trait-enabled dynamic vegetation model called ELM-FATES; testing drivers and representations of vegetation competition and productivity involving nutrient availability and plant hydraulic stress; nitrogen-fixing vegetation; evaluating model representation of current and trending distributions of Arctic vegetation types; and using observations to explore potential controls on rates of shrubification.  

You will be part of a team developing mechanistic and testable land models that can be applied across spatial and temporal scales and integrated with Earth System Models. Analyzing terrestrial biosphere responses to warming across the pan-Arctic domain is an important component of the research. We particularly encourage applicants with Arctic modeling experience or other Arctic experience.

What Is Required:

  • PhD in ecology, earth sciences, or a related field.
  • Background in terrestrial ecosystem ecology.
  • Strong mathematical skills.
  • Experience using land-surface biogeochemical models.
  • Computer coding skills to develop numerical representations of terrestrial ecosystem processes suitable for site-level and global scale models.
  • Experience in terrestrial ecosystem model development and algorithm coding.
  • Experience in application of models to analyze ecosystem processes (e.g. biogeochemistry, plant demography, carbon allocation).
  • Experience in dynamic and demographic modeling.
  • Experience in improving model prediction using benchmarking tools and uncertainty quantification.
  • Ability to carry out uncertainty quantification and calibration activities.
  • Excellent written and oral presentation skills.
  • Record of timely publications.
  • Demonstrated ability to work in teams and independently

For more details