The Climate Modeling Alliance (CliMA) is a coalition of scientists, engineers, and applied mathematicians from Caltech, MIT, the Naval Postgraduate School, and NASA's Jet Propulsion Laboratory. We are building the first Earth System Model (ESM) that automatically learns from diverse data sources to produce accurate climate predictions with quantified uncertainties. Our predictions will inform stakeholders as they plan resilient infrastructure, adapt supply chains to a changing climate, and assess the risks of climate-related hazards in their communities. At Caltech, we are seeking a Research Scientist to develop, test, and implement ESM components.
As a CliMA Research Scientist at Caltech, you will collaborate with a dynamic, multi-disciplinary team of curious and creative scientists, engineers, and applied mathematicians. You will advance the state of knowledge and contribute to the development of a data-informed ESM in one or more of several possible ways:
- Devising fast and scalable data assimilation and machine learning (DA/ML) algorithms that allow a computationally complex ESM to learn from diverse data sources, such as satellite observations or high-resolution simulations of turbulent flows.
- Developing physically informed parameterizations of subgrid-scale processes in the atmosphere that are suitable for DA/ML approaches, including models for boundary layer turbulence, clouds, and convection.
- Developing components of a land hydrology and biosphere model that uses DA/ML algorithms to learn from space-based observations of the hydrologic cycle and of the biosphere.
- Prototyping and building capabilities to run high-resolution large-eddy simulations on demand within a global ESM.
- Completed a doctoral degree in atmospheric sciences or physics.
- A strong physical, mathematical, and/or computational background.
- Programming experience in at least one general purpose language.
- Demonstrated effective written and verbal communication skills.
- At least 2 years of postdoctoral experience.
- Leadership experience of research projects, as demonstrated by publications.
- A doctoral degree in applied mathematics, computer science, engineering, statistics or a related field.
- Experience with high-performance parallel computing.
- Experience working in multi-disciplinary teams and interacting cross-functionally with a wide variety of people.
- Curriculum Vitae