University of Texas at Austin
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6 days ago
PhD or M.S. Opportunity in Compound Flooding and Flood Risk Assessment at UT Austin The University of Texas at Austin in United States
Degree Level
Master's, PhD
Field of study
Computer Science
Funding
One position is available and is expected to be supported through a research assistantship and/or teaching assistantship.
Deadline
Dec 1, 2026
Country
United States
University
University of Texas at Austin

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About this position
A graduate student opportunity is available for Ph.D. or M.S. study starting Fall 2027 at the COMPOUND Flood Lab in the Maseeh Department of Civil, Architectural and Environmental Engineering at The University of Texas at Austin.
The project focuses on compound flooding, debris–structure–wave interactions, and/or flood risk assessment, with research methods including numerical modeling, machine learning, and remote sensing. The post also highlights interest in applicants with experience in high-performance computing and in developing software or research workflows using large language models (LLMs).
The position is expected to be supported through a research assistantship and/or teaching assistantship. Applicants should have a background in Civil Engineering, Coastal Engineering, Ocean Engineering, Hydrology, Hydraulic Engineering, or a related field. For Ph.D. applicants, a master’s degree is preferred.
To apply, submit an application to the UT Austin graduate program in Civil, Architectural and Environmental Engineering by December 1, choose either EWRE or MUSE, and mention Prof. Lee in your Statement of Purpose. The post also encourages interested candidates to email [email protected] with the subject line Prospective Graduate Student and attach a CV highlighting relevant research experience and technical skills.
Funding details
One position is available and is expected to be supported through a research assistantship and/or teaching assistantship.
What's required
Applicants should have a background in Civil Engineering, Coastal Engineering, Ocean Engineering, Hydrology, Hydraulic Engineering, or a related field. A master's degree is preferred for Ph.D. applicants. Experience with numerical modeling tools such as ADCIRC, Delft3D, SFINCS, OpenFOAM, or MPM; machine learning methods such as PIML, GNNs, transformers, or neural operators; remote sensing; or high-performance computing is a plus. Experience developing software or research workflows using large language models is of particular interest.
How to apply
Apply to the graduate program in Civil, Architectural and Environmental Engineering at UT Austin by December 1. Select either EWRE or MUSE and mention Prof. Lee in your Statement of Purpose. You may also email [email protected] with the subject line "Prospective Graduate Student" and attach your CV.
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