RSA III - AI/ML Modeling of Land-Atmosphere Interactions

University of Texas at Austin • Austin, TX

4d • Onsite

About The Position

The RSA III will lead research on environmental challenges under meteorological extremes (hurricanes, heatwaves, droughts, and floods) and their impacts on resources in Texas. This includes integrating hydroclimatic, land and atmospheric datasets, applying advanced AI/ML approaches, and contributing to the development of digital twin frameworks. The duration of this position is 1 year from start date.

Requirements

• Bachelor's degree in Engineering and 4+ years of experience with a concentration in Civil and Environmental Engineering and Hydrological Foundational Knowledge, or Master’s degree in civil engineering, Environmental Science, Hydrology, or related field and 2+ years of research experience with particular focus on hydrology or hydrometeorology
• Demonstrated experience in large meteorological and hydrological data analysis, including extreme event assessments as evidenced by contributions to data repositories.
• Strong programming skills (Python, Bash) and experience with machine learning libraries (PyTorch, TensorFlow, scikit-learn), especially with HPC/cloud-based environments.
• Proficiency in developing websites or visualization portals (ReactJS)
• Proficiency in GIS software (ArcGIS, QGIS, GDAL, GeoPandas)
• Experience writing and contributing to developing grants for federal agencies
• Excellent written and oral communication skills.

Nice To Haves

• Ph.D. in Civil Engineering, Environmental Science, Hydrology, or related field + 3 years of research experience with particular focus on hydrology or hydrometeorology.
• 2+ years of postdoctoral researcher experience.
• Research experience applying AI/ML to hydrological prediction problems for Texas region.
• Prior work on coupled modeling frameworks and integration of observational, model, and remote sensing datasets for City-scale applications with WRF, SOLWEG or similar building resolving models.
• Experience in digital twin development or interdisciplinary projects linking hydrology, extremes.
• Record of peer-reviewed publications, invited talks, and grant proposal contributions.
• Self-motivated and collaborative with strong problem-solving and mentorship skills.

Responsibilities

• Conduct research on hydroclimatic extremes using large datasets, satellite remote sensing products, and regional/global climate model outputs.
• Develop and apply machine learning and hybrid AI methods to forecast hydrological and weather extremes
• Publish peer-reviewed papers and present findings at international conferences
• Contribute to grant proposal development and support the mentoring of students and interns.
• Development of Visualization portals or websites.
• Perform geospatial analysis and mapping using GIS and geostatistical tools to assess spatiotemporal variability in meteorological variables.
• Design and execute multi-model evaluation studies (e.g., WRF, HRLDAS, AI-NWP) for extreme weather and water variability predictions

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 251-500 employees