[ES_JOBS_NET] Project Leader, Program for Climate Model Diagnosis and Intercomparison (PCMDI), LLNL

[Bonfils, Celine J. W]

Dear Colleagues,

We are currently advertising for a position in climate science at the Lawrence Livermore National Laboratory (LLNL).
We would like to encourage all interested candidates to apply. Apologies for any cross-postings.

Project Leader, Program for Climate Model Diagnosis and Intercomparison (PCMDI)

Job Description
We have an opening for the Project Leader and Principal Investigator of the Program for Climate Model Diagnosis and Intercomparison (PCMDI), a major research activity funded by the DOE Office of Science. You will direct an internationally-recognized research effort in climate science, including climate model diagnostics, model performance metrics, and climate change detection and attribution research, and you will provide leadership and community support for international climate modeling activities. This position is in the Atmospheric, Earth and Energy Division.

Essential Duties
- Provide technical guidance, leadership and vision for PCMDI.
- Enhance the capabilities and status of PCMDI by leading world-class research that employs multi-model ensembles of climate simulations for evaluating, diagnosing, and improving models, including understanding climate variability and change.
- Champion PCMDI’s contributions to the international climate modeling community, and provide leadership in the design of multi-model experiments and development of modeling infrastructure requirements and standards.
- Serve as primary spokesperson for communications with program sponsors on research progress, budgets and new programmatic directions.
- Foster effective communication between PCMDI staff, division management and upper management.
- Publish research results in peer-reviewed journals and deliver presentations at scientific conferences.
- Manage project budget and scientific progress of PCMDI.
- Lead the triennial project proposal and review process.
- Perform other duties as assigned.

Qualifications
- PhD in a field closely related to climate science such as atmospheric science, oceanography, or applied mathematics, or the equivalent combination of education or related experience.
- Subject matter expertise with data standards and conventions for large multi-model archives of simulation output; advanced knowledge of computational infrastructure used for supporting model and observational data archives.
- Extensive experience performing cutting-edge research in the analysis and evaluation of climate model data.
- Possess a distinguished and sustained track record in research leadership within the international community.
- Expert interpersonal and collaboration skills, with a demonstrated ability to lead a research team, develop and share a vision, and work effectively individually and as part of a team.
- Expert verbal and written, communication and facilitation skills necessary to effectively advise senior management, external sponsors, and/or stakeholders on a broad range of issues related to climate science.
- An outstanding publication record in the peer-reviewed literature.
- A track record of involvement in international multi-model projects and assessments.

Desired Qualifications
- Significant knowledge and evidence of community leadership in a specialized area of climate research (e.g., atmospheric processes, energy budgets, physical oceanography, cryospheric processes, the hydrological cycle, climate change detection and attribution, or regional climate change).
- Extensive experience working effectively in a diverse work environment at a major national laboratory.

To apply, visit http://apptrkr.com/980466

LLNL is an affirmative action/ equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, protected veteran status, age, citizenship, or any other characteristic protected by law.



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