Postdoc Fellow: ML Ocean State Estimation & Uncertainty

1000scholars; San Diego (CA); On-site; USD 65,000 - 85,000; Full time

Job summary

UCSD Environmental Fluid Dynamics Lab in the UCSD Department of Mechanical and Aerospace Engineering invites applications for a postdoctoral fellowship focused on machine learning-based ocean state estimation. The position aims to develop data-driven tools with uncertainties for near-field prediction of marine conditions, including applications to mCDR and aquaculture, beginning Spring/Summer 2026.

Candidates should have experience in data-driven modeling, scientific ML, or coastal ocean

Qualifications

• Experience with data-driven modeling and machine learning for ocean applications.
• Familiarity with reduced-order modeling and large-data workflows.
• Interest in applying methods to ocean state estimation with quantified uncertainties.

Responsibilities

• Develop and apply reduced-order modeling approaches using spatiotemporal decompositions of large high-resolution simulation datasets.
• Develop and train machine learning architectures using reduced-order predictions with heterogeneous data.
• Integrate data-driven methods into a framework for uncertainty-aware ocean state estimation.
• Apply and validate the framework using datasets at experimental sites.
• Publish research in peer-reviewed journals and present results at conferences.
• Mentor graduate and undergraduate students in the Environmental Fluid Dynamics Lab.

Skills

Data-driven modeling

Scientific machine learning

Coastal ocean physics

Tools

Reduced-order modeling

Job description

UCSD Environmental Fluid Dynamics Lab in the UCSD Department of Mechanical and Aerospace Engineering invites applications for a postdoctoral fellowship focused on machine learning-based ocean state estimation. The position aims to develop data-driven tools with uncertainties for near-field prediction of marine conditions, including applications to mCDR and aquaculture, beginning Spring/Summer 2026.

Candidates should have experience in data-driven modeling, scientific ML, or coastal ocean