Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions. We thrive on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community.
Climate change projections continue to be marred by large uncertainties but breakthroughs in their accuracy are within reach, thanks to recent advances in the computational and data sciences and in the availability of Earth observations from space and from the ground. Caltech and partner institutions are developing a new Earth system modeling platform to harness these advances. It will fuse an Earth system model (ESM) with global observations and targeted local high-resolution simulations of clouds, turbulence, and other elements of the Earth system.
You will collaborate with a dynamic, multi-disciplinary team of scientists, engineers, and applied mathematicians, spanning Caltech, the NASA Jet Propulsion Laboratory, the Massachusetts Institute of Technology, and the Naval Postgraduate School.
As a Software Engineer, you will:
- Work on a fast-paced, high-profile project with a significant opportunity for impacting Earth system modeling worldwide.
- Design, develop, test, deploy, maintain, and improve the ESM platform software.
- Be a hands-on coder applying the best industry standards for code health, scalability, and robustness.
- Develop physic-focused models and physics-based test.
- BS degree in computer science or a science or engineering field.
- Experience developing large software projects in a distributed fashion, e.g., contributing to an open source project with distributed contributors.
- Experience working with high-performance computing systems including many core processors and accelerators.
- Experience with at least two general purpose programming languages (e.g., C/C++, C#, Objective C, Python, Fortran).
- A graduate degree in computer science or a science or engineering field.
- Experience in either computational fluid dynamics or machine learning or both.
- Experience with Navier-Stokes equations, numerical methods, and partial differential equations.
- Familiarity with atmospheric thermodynamics and or radiation.
- Experience working in multi-disciplinary teams and interacting cross-functionally with a wide variety of people.