Postdoctoral Fellow: Ocean State Estimation with ML

UC San Diego Academic Jobs; San Diego (CA); On-site; USD 69,073 - 71,632; Full time

Job summary

UC San Diego Academic Jobs seeks a Moore Postdoctoral Fellow for research in machine learning-based ocean state estimation within the Environmental Fluid Dynamics Lab. This role includes developing data-driven tools for enhancing prediction efficiency in marine operations and mentoring students.

The position requires a doctoral degree in engineering or related fields, with a salary range of $69,073 – $71,632. Responsibilities include collaborative research, publishing findings, and integrating advanced modeling approaches.

Qualifications

• Doctoral degree in engineering, oceanography, or a related field.
• Experience in data-driven modeling, machine learning, and/or fluid mechanics.
• Excellent written and oral communication skills.

Responsibilities

• Develop reduced-order modeling approaches using high-resolution datasets.
• Train machine learning architectures with observational data.
• Integrate methods for uncertainty-aware ocean state estimation.
• Validate framework using experimental datasets.
• Publish research and present at conferences.
• Mentor students.

Skills

Data-driven modeling

Machine learning

Fluid mechanics

Numerical fluid dynamics

Team collaboration

Excellent communication

Education

Doctoral degree in engineering or related field

Job description

UC San Diego Academic Jobs seeks a Moore Postdoctoral Fellow for research in machine learning-based ocean state estimation within the Environmental Fluid Dynamics Lab. This role includes developing data-driven tools for enhancing prediction efficiency in marine operations and mentoring students.

The position requires a doctoral degree in engineering or related fields, with a salary range of $69,073 – $71,632. Responsibilities include collaborative research, publishing findings, and integrating advanced modeling approaches.