Openings: Positions

  • Research Scientists, Postdoctoral Scholars, and Software Engineers in Data-Informed Earth System Modeling

    Within the Climate Modeling Alliance (CliMA), we regularly (but not always) have open positions for research scientists, software engineers, and postdoctoral scholars, to contribute to an ambitious and innovative Earth system modeling project. The goal is to develop the first Earth system model (ESM) that automatically learns from diverse data sources (e.g., observations from space and data generated computationally in high-resolution simulations) and produces accurate climate predictions with quantified uncertainties.

  • PhD Projects in Climate Dynamics

    We always seek knowledgable and motivated graduate students for PhD projects in the climate sciences. Possible projects may address questions, for example, in large-scale dynamics such as, How do global precipitation patterns change under global warming? What shapes the trajectories and intensities of midlatitude storms? Or they may address questions in smaller-scale dynamics such as, How does cloud cover change under global warming? How can we improve the parameterization of clouds in climate models? One focus currently is the design of Earth system models that learn from observations and high-resolution simulations using methods from data assimilation and machine learning. There are opportunities for PhD students with strong computational backgrounds in this area, jointly advised by Andrew Stuart in Computing and Mathematical Sciences.

    PhD students need to have an undergraduate degree or equivalent in physics, mathematics, engineering, the atmospheric sciences, or a related field. A solid background in mathematics and physics is generally more important than prior experience in the atmospheric or climate sciences.

    If you are interested in a PhD project, please contact Tapio Schneider (e-mail: or apply directly to Caltech‘s PhD program in Environmental Science and Engineering. The deadline for applications is January 1.