Te Pei
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Fully Funded PhD in Urban Flood Modeling and Scientific Machine Learning Stony Brook University in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD position with full financial support including tuition support, a stipend, and health insurance.
Country
United States
University
Stony Brook University
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About this position
Fully funded PhD opportunity in Urban Flood Modeling and Scientific Machine Learning at Stony Brook University (Department of Civil Engineering, New York, USA).
The position is in the research group of Te Pei, Assistant Professor in Civil Engineering. The project focuses on computational urban flood modeling with opportunities to combine hydrologic and hydrodynamic modeling, geospatial data, and scientific machine learning for water-related systems.
Research topics include urban flooding and hydrology, urban drainage and inundation modeling, computational and data-driven flood prediction, and machine learning/deep learning methods for flood and water systems. Applicants with training in hydrology, hydraulics, water resources engineering, civil/environmental engineering, or related fields are encouraged to apply.
Helpful experience includes flood or urban drainage modeling, hydrodynamic or numerical modeling, scientific computing and programming, and GIS/geospatial data analysis. Machine learning experience is welcome but not required.
The position is fully funded and includes tuition support, a stipend, and health insurance. The expected start date is Spring 2027 or Fall 2027.
To apply, email [email protected] with the subject line PhD Application – Urban Flood Modeling – [Your Name]. Include your CV, transcripts, a brief description of your research experience and interests, English proficiency scores if applicable, and any relevant publications, research samples, or code repositories.
Funding details
Fully funded PhD position with full financial support including tuition support, a stipend, and health insurance.
What's required
Applicants should have academic or research training in hydrology, hydraulics, water resources engineering, civil/environmental engineering, or a closely related field. Experience in flood or urban drainage modeling, hydrodynamic or numerical modeling, scientific computing and programming, or GIS/geospatial data analysis is especially valuable. Machine learning or deep learning experience is a plus but not required. Applicants should include English proficiency scores if applicable, along with CV, transcripts, a brief research summary, and any relevant publications, research samples, or code repositories.
How to apply
Email the supervisor with the subject line 'PhD Application – Urban Flood Modeling – [Your Name]'. Attach your CV, transcripts, a brief description of your research experience and interests, English proficiency scores if applicable, and any relevant publications, research samples, or code repositories.
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