Graduate Research Fellow: Compound Flood Modeling & ML

The University of Texas at Austin; Austin (TX); On-site; USD 24,000 - 36,000; Part time

Job summary

The University of Texas at Austin's COMPOUND Flood Lab seeks a motivated graduate student (Ph.D. or M.S.) to start in Fall 2027. Research areas include compound flooding, debris–structure–wave interactions, and flood risk assessment using numerical modeling, machine learning, and remote sensing.

Applicants from Civil/Coastal/Ocean/Hydrology/Hydraulic Eng. are encouraged; Ph.D. applicants with a master’s degree are preferred.

Qualifications

• Ph.D. or M.S. in Civil/Environmental Engineering; master’s preferred for Ph.D. applicants.
• Experience with numerical modeling, ML, remote sensing, or HPC is a plus.
• Interest in LLM-based research workflows and related software is desirable.

Responsibilities

• Join COMPOUND Flood Lab and contribute to fall 2027 onboarding.
• Conduct research on compound flooding and related interactions using modeling and ML.
• Collaborate with faculty and students; pursue RA/TA opportunities and disseminate results.

Skills

Numerical modeling

Machine learning

Remote sensing

High-performance computing

Education

Ph.D. in Civil Engineering

M.S. in Civil Engineering

Tools

ADCIRC

Delft3D

OpenFOAM

MPM

SFINCS

Job description

The University of Texas at Austin's COMPOUND Flood Lab seeks a motivated graduate student (Ph.D. or M.S.) to start in Fall 2027. Research areas include compound flooding, debris–structure–wave interactions, and flood risk assessment using numerical modeling, machine learning, and remote sensing.

Applicants from Civil/Coastal/Ocean/Hydrology/Hydraulic Eng. are encouraged; Ph.D. applicants with a master’s degree are preferred.