Job: Postdoctoral Research Associate: Exploring Key Factors for a Near-zero Emission Energy Transition

Department: DGE – Global Ecology

Salary: TBD Competitive

Location: Stanford, CA

We are developing a group of collaborating researchers who seek to explore key factors that could help facilitate a transition to a near-zero emission energy system. As the Carnegie Energy Innovation project (, we engage in a collection of projects, which postdocs are expected to lead. Our work typically falls into four related areas:

  1. Schematic energy-system modeling
  2. Schematic economic modeling
  3. Geophysical modeling
  4. Energy and climate-related analysis

Examples of current projects include: (1) A schematic energy system modeling effort aimed at understanding the range of potentially feasible near-zero emission energy systems, what would have to become true to make feasible different system architectures, and the value of technical innovation. (2) A schematic economic modeling effort aimed at understanding the role of efficiency improvements in affecting carbon dioxide emissions and economic growth. (3) A geophysical modeling effort aimed at understanding efficacy and possible unintended consequences of regional-scale wind farms. (4) An analysis of factors that would affect the potential climate benefit of possible technological innovations. We are also in the process of organizing an international meeting on balancing climate and development objectives in the poorest countries of the world.

Postdocs are free to work on a broad range of topics within this broad general domain. Examples of such studies published so far this year include: Shayegh et al. (Evaluating relative benefits of different types of R&D for clean energy technologies, Energy Policy, 2017), Cao et al. (Simultaneous stabilization of global temperature and precipitation through cocktail geoengineering, GRL, 2017), Clack et al. (Evaluation of a proposal for reliable low-cost grid power with 100% wind, water, and solar, PNAS, 2017), Wang et al. (Will the use of a carbon tax for revenue generation produce an incentive to continue carbon emissions? ERL, 2017), Ahbe and Caldeira (Spatial Distribution of Generation of Lorenz’s Available Potential Energy in a Global Climate Model, J Clim., 2017).

This position will involve working with Ken Caldeira at the Carnegie Institution for Science Department of Global Ecology on the Stanford University campus. Caldeira has a physical science background, but we are collaborating closely with (and hiring!) people who have deeper experience in energy system and/or economic modeling. Another option would be to work at University of California (Irvine) with Steve Davis as principal mentor (

Successful candidates will play a major role in planning and executing these investigations and communicating the results through peer-reviewed publications and direct engagement with public and private technology investment and policy decision makers. The initial term will be for one year with the potential for renewal for a second year up to a maximum of four years.

Candidates with a PhD in science, engineering or economics, or comparable experience in quantitative analysis, are particularly encouraged to apply. Achievement in the area of scientific publication, or comparable evidence of being able to complete high quality work in a timely manner, is a primary filter determining which applications receive greater consideration. Positions are available now; start date is flexible but Spring or Summer of 2018 would be ideal. Carnegie Institution post-docs have access to most Stanford facilities. Compensation for this position includes a competitive salary and comprehensive benefits.

Informal inquiries about these positions can be made by emailing Ken Caldeira at  Formal applications for employment must be submitted by clicking on the bar below, and must include both a cover letter and CV.

Carnegie is an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, veteran status, disability or any other protected status in accordance with applicable laws.