Postdoctoral Scholar in Data-Informed Earth System Modeling at Caltech
Climate change projections continue to be marred by large uncertainties. But new tools from computational science, data assimilation, and machine learning have brought rapid progress in this important area within reach.
The California Institute of Technology (Caltech) invites applications for a postdoctoral scholar position in data-informed Earth system modeling. The postdoctoral scholar will develop data assimilation and machine learning algorithms for Earth system models, to allow them to learn systematically from diverse data sources, such as satellite observations or high-resolution simulations of turbulent flows in targeted regions.
Candidates are expected to have completed a doctoral degree in applied mathematics, atmospheric or oceanic sciences, computer science, engineering, physics, statistics or a related field at the time of the appointment. A strong mathematical and computational background is essential. Experience with high-performance computing and large datasets is desirable.
For further information about the position, please contact Tapio Schneider (firstname.lastname@example.org) or Andrew Stuart (email@example.com), or visit climate-dynamics.org.
Applications with a curriculum vitae, a one-page statement of research interests, and three letters of recommendation should be emailed to Bronagh Glaser (firstname.lastname@example.org). Review of applications will begin on January 15 and will continue until the positions are filled. The position is for two years, with appointment in the second year contingent on progress in the first year.
Caltech and JPL are equal opportunity employers, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin, disability status, protected veteran status, or any other characteristic protected by law.