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Fangfang Yao
1 year ago
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Water resources research University of South Florida (USF) 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. The funding covers stipend and tuition for the duration of the PhD program.
Deadline
Expired
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 a PhD student for interdisciplinary research in water resources using advanced geospatial technologies. The lab leverages satellite observations, remote sensing, and AI/ML to address global water crises and study the water cycle at regional and global scales. Recent research from the lab has been featured in Science Magazine.
The position is ideal for candidates with a strong background in remote sensing or hydrology, geospatial data processing skills (Python or R), and an interest in hydrological studies. Preferred qualifications include publication experience, familiarity with InSAR/LiDAR sensors or AI/ML, and big data analytics experience. The successful candidate will receive at least four years of funding through teaching and research assistantships, covering stipend and tuition.
The University of South Florida is a top 50 public university and AAU member, located in Tampa, Florida, offering a vibrant campus life and access to local attractions. The application deadline is January 7, 2026, with late inquiries considered for strong candidates. To apply, send a CV, references, and a research introduction to Dr. Fangfang Yao at [email protected].
Funding details
Selected candidates will receive at least four years of funding through a combination of teaching and research assistantships. The funding covers stipend and tuition for the duration of the PhD program.
What's required
Applicants should have a strong background in remote sensing or hydrology, interest in regional to global hydrological studies, experience with geospatial data processing using Python or R, and strong communication and scientific writing skills. Preference is given to candidates with publication experience in peer-reviewed journals, familiarity with advanced InSAR/LiDAR sensors or AI/ML, and experience in big data analytics (HPC or Google Earth Engine). An advanced degree (Master's or JD) is required. English language proficiency is necessary.
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Professors
Assistant Professor
United States
Research Interests
Hydrology
Reservoir Engineering
Remote Sensing
Lidar Technology
Environmental Science
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.