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

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

Hiring Department: Bureau of Economic Geology

Position Open To: All Applicants

Weekly Scheduled

Hours:

40

FLSA Status: Exempt

Earliest

Start Date:

Immediately

Position Duration: Expected to Continue Until Dec 15, 2026

Location: PICKLE RESEARCH CAMPUS

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.

• 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.
• Develop 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.

• 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, Tensor Flow, scikit‑learn), especially with HPC/cloud‑based environments.
• Proficiency in developing websites or visualization portals (React
  
  JS).
• Proficiency in GIS software (ArcGIS, QGIS, GDAL, Geo Pandas).
• Experience writing and contributing to developing grants for federal agencies.
• Excellent written and oral communication skills.

• 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.

$80,000+ depending on experience

• May work in all weather conditions.
• May work in extreme temperatures.
• May work around chemical fumes.
• May work around standard office conditions.
• May work around chemicals.
• May work around electrical and mechanical hazards.
• Repetitive use of a keyboard at a workstation.
• Climbing of stairs.
• Climbing of ladders.
• Lifting and moving.
• Occasional weekend, overtime, and evening work to meet deadlines.
• Occasional fieldwork as necessary.

• Resume/CV.
• 3 work references with their contact information.
• Letter of interest.

Applicants who are not current university employees or contingent workers must submit their resume and required materials via the provided application portal. Once submitted, changes cannot be made.

Current university employees or contingent workers must apply within Workday, sharing their resume and responding to application questions to upload additional…