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.
Duties/Responsibilities
- Conduct comprehensive literature reviews and collaborate with the Principal Investigator (PI) to identify research gaps related to the proposed research topic. (30%)
- Design and implement the proposed model, and conduct experiments to establish proof of concept. (40%)
- Prepare and write the manuscript for submission to a peer-reviewed journal. (30%)
Relevant/Preferred Education, Experience, Licensure, Certification in Position
- 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
Knowledge, Skills, Abilities and/or Competencies
- 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 (e.g., shapefiles, .shp) and Raster data (e.g., GeoTIFF)
- Strong programming skills (e.g., Python)
- Ability to work independently and collaboratively in a research environment
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