NGEE-Arctic Vegetation Modeling Postdoctoral Scholar

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 You Will Do:

• Develop and apply new representations of vegetation demography and ecosystem processes and implement them in numerical process-based land models.
• Develop and apply mathematical and/or conceptual models for terrestrial processes across a range of spatial and temporal scales.
• Explore the impact of climate change and disturbance on shrub dynamics, carbon cycling, and plant trait distributions in the Arctic.
• Simulate seedling processes at the site scale using NGEE observations from surveys and experiments.
• Evaluate the extent and drivers of Arctic shrubification.
• Evaluate parameter and structural uncertainty in land models.
• Work creatively, independently, and productively.
• Work as a member of a large multidisciplinary research team.
• Publish peer-reviewed journal articles and present work at scientific conferences.
• Contribute to progress reports and team deliverables.

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.

Additional Desired Qualifications:

• Expertise in vegetation modeling, terrestrial ecological processes, biogeochemistry, and/or plant-competition.
• Arctic modeling experience or other Arctic research experience.
• Ability to handle large data sets.
• Experience with benchmarking and uncertainty quantification.

Required Materials (To be submitted through LBNL recruitment system):

• Curriculum vitae
• Cover letter
• 1-2 of your publications

The posting shall remain open until the position is filled.

Notes: 

• This is a full time, 1 year, postdoctoral appointment with the possibility of renewal for up to three years based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 4 years paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
• Full-time, M-F, exempt (monthly paid) from overtime pay.
• 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.
• Work will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

How To Apply

Apply directly online at http://50.73.55.13/counter.php?id=158196 and follow the on-line instructions to complete the application process. 

Berkeley Lab (LBNL, http://www.lbl.gov/) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.

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 You Will Do:

• Develop and apply new representations of vegetation demography and ecosystem processes and implement them in numerical process-based land models.
• Develop and apply mathematical and/or conceptual models for terrestrial processes across a range of spatial and temporal scales.
• Explore the impact of climate change and disturbance on shrub dynamics, carbon cycling, and plant trait distributions in the Arctic.
• Simulate seedling processes at the site scale using NGEE observations from surveys and experiments.
• Evaluate the extent and drivers of Arctic shrubification.
• Evaluate parameter and structural uncertainty in land models.
• Work creatively, independently, and productively.
• Work as a member of a large multidisciplinary research team.
• Publish peer-reviewed journal articles and present work at scientific conferences.
• Contribute to progress reports and team deliverables.

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.

Additional Desired Qualifications:

• Expertise in vegetation modeling, terrestrial ecological processes, biogeochemistry, and/or plant-competition.
• Arctic modeling experience or other Arctic research experience.
• Ability to handle large data sets.
• Experience with benchmarking and uncertainty quantification.

Required Materials (To be submitted through LBNL recruitment system):

• Curriculum vitae
• Cover letter
• 1-2 of your publications

The posting shall remain open until the position is filled.

Notes: 

• This is a full time, 1 year, postdoctoral appointment with the possibility of renewal for up to three years based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 4 years paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
• Full-time, M-F, exempt (monthly paid) from overtime pay.
• 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.
• Work will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.

How To Apply

Apply directly online at http://50.73.55.13/counter.php?id=158196 and follow the on-line instructions to complete the application process. 

Berkeley Lab (LBNL, http://www.lbl.gov/) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.

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 (https://www.dol.gov/ofccp/PayTransparencyNondiscrimination.html).  Click here (https://www.dol.gov/ofccp/PayTransparencyNondiscrimination.html) to view the poster: “Equal Employment Opportunity is the Law”.

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 (https://www.dol.gov/ofccp/PayTransparencyNondiscrimination.html).  Click here (https://www.dol.gov/ofccp/PayTransparencyNondiscrimination.html) to view the poster: “Equal Employment Opportunity is the Law”.