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Song Shu

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PhD Studentship in Remote Sensing and Hydrology at Kansas State University Kansas State University in United States

Degree Level

PhD

Field of study

Computer Science

Funding

RA/TA support is available based on merit.

Deadline

Nov 15, 2026

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Country

United States

University

University of Kansas

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Keywords

Computer Science
Environmental Science
Remote Sensing
Geography
Hydrology
Artificial Intelligence
Civil Engineering
Earth Science
Water Resource Management
Statistics
ML

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About this position

PhD opportunity in Remote Sensing & Hydrology at Kansas State University

Associate Professor Song Shu at Kansas State University is recruiting 1–2 highly motivated PhD students to join the School of Earth & Environment, with a planned start in Fall 2027.

The research group works on surface water hydrology, water resources, and water storage dynamics using satellite and UAV/drone remote sensing, GIS, AI, and advanced computational methods. Potential topics include lake and river hydrology, water-level and surface-water storage dynamics, satellite altimetry, multispectral and SAR imagery, LiDAR, UAV/drone remote sensing, AI and machine learning, snow, water quality, bathymetry, and erosion.

Students with backgrounds in hydrology, water resources, remote sensing, GIS, geography, environmental science, engineering, computer science, or related fields are encouraged to apply. Experience with remote sensing/altimetry, LiDAR, UAVs, spatial data analysis, programming, AI/ML, or cloud-based computing is highly desirable.

Funding support includes RA/TA support based on merit.

Application timeline: initial materials are due November 15, 2026; shortlisted candidates will be invited for Zoom interviews in late November to early December; the graduate school application deadline is January 8, 2027.

To apply, email [email protected] with a CV, personal statement, and unofficial transcript.

Funding details

RA/TA support is available based on merit.

What's required

Applicants should have a background in hydrology, water resources, remote sensing, GIS, geography, environmental science, engineering, computer science, or a related field. Experience with remote sensing/altimetry, LiDAR, UAVs, spatial data analysis, programming, AI/ML, or cloud-based computing is highly desirable. The post is for highly motivated PhD students.

How to apply

Email [email protected] with your CV, personal statement, and unofficial transcript. Initial application materials are due November 15, 2026. Shortlisted candidates will then be invited for Zoom interviews, and the graduate school application deadline is January 8, 2027.

More information can be found here

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