Gengchen Mai
Top university
5 months ago
Geospatial AI UT Austin in United States
Degree Level
PhD
Field of study
Computer Science
Funding
PhD students will be fully funded through a combination of National Science Foundation grants (no US citizenship requirement for some grants), NSF PhD Fellowships focusing on Ethical GeoAI (US Citizen or Green Card required), and UT Geography Teaching Assistantships. Financial support is provided as a teaching assistant or research assistant, contingent on satisfactory performance.
Deadline
Expired
Country
United States
University
University of Texas at Austin
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Where to contact
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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, is recruiting 2-3 PhD students to begin in Fall 2026. The lab specializes in Geospatial AI (GeoAI), spatially explicit machine learning, deep learning, knowledge graphs, and spatial data mining. Students will collaborate on cutting-edge projects with academic and industry partners, including Google, Google Research, OpenAI, and Esri.
The University of Texas at Austin is a top-ranked public research university, and Dr. Mai is an Assistant Professor in the Department of Geography and the Environment, with extensive experience in both academia and industry. Admitted students will be fully funded through NSF grants, fellowships, and teaching assistantships, with opportunities for industry internships.
Applicants should have a background in GIScience, remote sensing, computer science, or related fields, proficiency in programming and spatial analysis tools, and strong English skills. To apply, send a CV and brief statement to Dr. Mai.
For more information, visit the lab's recruitment page.
Funding details
PhD students will be fully funded through a combination of National Science Foundation grants (no US citizenship requirement for some grants), NSF PhD Fellowships focusing on Ethical GeoAI (US Citizen or Green Card required), and UT Geography Teaching Assistantships. Financial support is provided as a teaching assistant or research assistant, contingent on satisfactory performance.
What's required
Applicants must have a bachelor's or master's degree in GIScience, remote sensing, computer science, information science, or a related field before August 2026. They should have a strong passion for GIScience and GeoAI research, be familiar with at least one programming language (e.g., Java, C++, Python), and have experience with spatial analysis and mapping tools (e.g., ArcGIS or QGIS). Research experience in machine learning and AI is a plus but not required. Applicants must be fluent in spoken English.
How to apply
Send your CV and a brief statement (no more than 300 words) to Dr. Gengchen Mai at [email protected]. For more details, visit the provided lab recruitment page. Contact Dr. Mai with any questions.
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