Publisher
source

Gengchen Mai

Top university

7 months ago

Geospatial AI UT Austin in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

December 31, 2026
Country flag

Country

United States

University

University of Texas at Austin

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More information can be found here

Official Email

[email protected]

Keywords

Computer Science
Environmental Science
Information Technology
Deep Learning
Remote Sensing
Geography
Spatial Analysis
Knowledge Representation
Giscience
Geospatial Information
Machine learning

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

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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