The University of Texas at Austin is seeking to address critical environmental and Earth system challenges by leveraging cutting-edge artificial intelligence and data science.
Requirements
- Demonstrated Programming Skills And Experience With Data Analysis
- Interest in artificial intelligence, machine learning, data science, remote sensing, or environmental/Earth system science
Responsibilities
- Machine learning and causality inference in environmental contexts
- Development and application of foundation AI models
- Analysis of remote sensing and geospatial data
- Environmental data science for hazard and risk modeling
- Terrestrial ecosystem modeling and vegetation dynamics
- Human-environment and land-atmosphere interactions
Other
- A strong background in quantitative disciplines such as computer science, statistics, mathematics, engineering, environmental science, or related fields
- Intellectual curiosity and a drive to pursue innovative research questions
- The ability to work both independently and collaboratively within a diverse team
- Motivation to contribute to impactful research at the intersection of technology and environmental science
- Applicants must also meet the admission requirements of the UT Austin Graduate School.
