Gengchen Mai
Top university
6 months ago
Geospatial AI The University of Texas at Austin in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
December 31, 2026Country
United States
University
University of Texas at Austin

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About this position
The Spatially Explicit Artificial Intelligence (SEAI) Lab at the University of Texas at Austin, led by Dr. Gengchen Mai (Assistant Professor, Department of Geography and the Environment), is recruiting 2–3 PhD students to begin in Fall 2026. The lab focuses on cutting-edge research in Geospatial Artificial Intelligence (GeoAI), including spatially explicit machine learning, deep learning, knowledge graphs, and spatial data mining. Students will have opportunities to collaborate with leading researchers from academia and industry, including Google, Google Research, OpenAI, and Esri, and may intern at high-tech companies.
The University of Texas at Austin is a top-ranked public research university. Admitted PhD students will be funded through National Science Foundation grants, NSF PhD Fellowships (some requiring US citizenship or permanent residency), and UT Geography Teaching Assistantships. Applicants should hold a bachelor's or master's degree in GIScience, remote sensing, computer science, information science, or a related field by August 2026, have a passion for GIScience and GeoAI, be familiar with programming languages (Java, C++, Python), and spatial analysis tools (ArcGIS, QGIS).
Research experience in machine learning and AI is a plus but not required. English fluency is required. To apply, send your CV and a brief statement to Dr. Mai at [email protected].
For more information, visit https://gengchenmai.github.io/.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
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