University of South Florida
1 month ago
Assistantship
Ph.D. student positions in hydrological remote sensing at University of South Florida University of South Florida in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Selected candidates will receive at least four years of funding through a combination of teaching and research assistantships.
Deadline
Jan 7, 2027
Country
United States
University
University of South Florida

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About this position
The Hydrological Remote Sensing Lab (HydroRS) at the University of South Florida is recruiting Ph.D. students for research in hydrological remote sensing starting Spring 2027 or Fall 2027.
The lab works on interdisciplinary water resources research using satellite observations, remote sensing, AI/ML, and geospatial technologies to study the changing water cycle and water crises at regional to global scales. Example topics include hydrological extremes, trends and drivers of freshwater storage, human footprint on water, and changing water towers such as snowpacks and glaciers.
Applicants should have a strong background in remote sensing or hydrology, experience with geospatial data processing in Python or R, and strong communication and scientific writing skills. Preference is given to candidates with publication experience and familiarity with advanced SAR and LiDAR missions such as SWOT, ICESat-2, and NISAR.
Funding is available for at least four years through teaching and research assistantships. The position is based at the Tampa campus of the University of South Florida in the United States.
To apply, send a CV, three references, and a personal statement to Dr. Fangfang Yao, then complete the formal graduate application through the USF website. Spring 2027 applications are due by October 15, 2026, and Fall 2027 applications are due by January 7, 2027.
Funding details
Selected candidates will receive at least four years of funding through a combination of teaching and research assistantships.
What's required
Applicants should have a strong background in remote sensing or hydrology, interest in regional- to global-scale hydrological studies, experience with geospatial data processing using Python or R, and good communication and scientific writing skills. Preference is given to candidates with a publication record in remote sensing or hydrology and familiarity with advanced SAR and LiDAR sensors, especially SWOT, ICESat-2, and NISAR. The post is for Ph.D. students starting Spring 2027 or Fall 2027.
How to apply
Email Dr. Fangfang Yao with a full CV, contact information for three references, and a personal statement as attachments to discuss the opportunity. Then submit the formal application through the USF graduate application website by the stated deadline. For Fall 2027, contact the supervisor as soon as possible, ideally before October 7, 2026.
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