Postdoc position in ML-based ocean state estimation

The Environmental Fluid Dynamics Lab in the Department of Mechanical and Aerospace Engineering at UCSD invites applications for a postdoctoral fellowship funded by the Gordon and Betty Moore Foundation focused on the topic of machine learning-based ocean state estimation to begin in Spring/Summer 2026. The successful applicant will develop and implement data-driven tools, underpinned by scientific machine learning and reduced- order modeling, for ocean state estimation with quantified uncertainties. The central aim is to increase the efficiency and accuracy of near-field prediction of physical and biological conditions for marine operations including marine carbon dioxide removal (mCDR) and aquaculture. The ideal candidate will have experience in two or three of the focal areas: data driven modeling, scientific machine learning or coastal ocean physics; and will have an interest in applying these towards ocean applications. The postdoc will work directly with Dr. Geno Pawlak Tejada, Dr. Boris Kramer and Dr. Oliver Schmidt at the Department of Mechanical and Aerospace Engineering and will also collaborate with co-investigators at Stanford University. Please visit the following webpage for application instructions and deadlines. https://efdlab.ucsd.edu/home/research/moore-foundation-pd-fellow