Research Assistant

Research Assistant

Position Summary:

The student will work under the supervision of Dr. Tao Liu to conduct research and contribute to scholarly publications on AI applications using remote sensing data. The primary focus will be on developing and applying geospatial/remote sensing foundation models for land cover classification and monitoring key forest metrics.

• Conduct comprehensive literature reviews and collaborate with the Principal Investigator (PI) to identify research gaps related to the proposed research topic.
• Design and implement the proposed model, and conduct experiments to establish proof of concept.
• Prepare and write the manuscript for submission to a peer‑reviewed journal.

• Graduate student (Master’s or Ph.D.) in Computer Science, Engineering, Artificial Intelligence, Geospatial Science, or a related field.
• Experience developing deep learning models using PyTorch.
• Experience applying machine learning or deep learning methods to remote sensing imagery.

• Proficiency in deep learning frameworks (preferably PyTorch).
• Familiarity with remote sensing data processing and analysis.
• Basic knowledge of GIS concepts and workflows.
• Experience working with geospatial data formats, including vector data (shape files, .shp) and raster data (GeoTIFF).
• Strong programming skills (Python).
• Ability to work independently and collaboratively in a research environment.

The University of Georgia is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, genetic information, national origin, race, religion, sex, veteran status or other protected status. Persons needing accommodations or assistance with the accessibility of materials related to this search are encouraged to contact Central HR (hrweb).