PhD in Hydrologic Modeling & Scientific ML

European Geosciences Union (EGU); Princeton (NJ); On-site; USD 32,000 - 42,000; Full time

Job summary

Princeton University is seeking Ph.D. students to join the Civil and Environmental Engineering and High Meadows Environmental Institute in Fall 2027.

The research spans hydrologic modeling, Earth system processes, and scientific machine learning, with a focus on the Tiger-HLM framework. Applicants should have strong quantitative skills and a background in engineering, earth or environmental science, or related fields.

Qualifications

• Candidates must have a degree in engineering, earth or environmental science, applied mathematics, computer science, physics, statistics, or a related discipline.
• Strong quantitative and computational skills are expected.
• Experience with hydrologic modeling, machine learning, scientific programming, numerical methods, and/or analysis of large geophysical datasets is desirable.

Responsibilities

• Join a research group in Civil and Environmental Engineering and High Meadows Environmental Institute at Princeton University.
• Contribute to hydrologic prediction research and develop Tiger-HLM modeling framework.
• Explore scientific ML approaches and parameterizations for Earth system processes.

Skills

Hydrologic modeling

Machine learning

Scientific programming

Numerical methods

Geophysical data analysis

Education

Master's degree (engineering/earth/environmental science/applied math/CS/physics/statistics)

Tools

Python

MATLAB

TensorFlow/PyTorch

Job description

Princeton University is seeking Ph.D. students to join the Civil and Environmental Engineering and High Meadows Environmental Institute in Fall 2027.

The research spans hydrologic modeling, Earth system processes, and scientific machine learning, with a focus on the Tiger-HLM framework. Applicants should have strong quantitative skills and a background in engineering, earth or environmental science, or related fields.