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PhD Positions in AI, Hydrometeorology, and Earth System Science at Texas Tech University Texas Tech University in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Two PhD openings are advertised for Spring 2027 and Fall 2027. The post does not specify stipend, tuition coverage, or whether the positions are fully funded.
Country
United States
University
Texas Tech University
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About this position
Texas Tech University’s Department of Geosciences, Atmospheric Science Program, is advertising 2 PhD openings in Dr. Jiangtao Liu’s lab for Spring 2027 and Fall 2027.
The research theme sits at the intersection of AI, hydrometeorology, and Earth system science, with a focus on linking atmospheric and hydrologic processes and using multimodal Earth observations for flood prediction. The lab highlights four possible directions: AI for weather-water prediction, multimodal observations and geoscience foundation models, physics-informed AI, and extremes and land-atmosphere-water interactions.
Relevant backgrounds include hydrology, water resources, atmospheric science, environmental science, civil engineering, remote sensing/GIS, geoscience, computer science/data science, and applied math. Desired skills include Python, scientific computing, machine learning/deep learning, hydrologic or atmospheric modeling, remote sensing, and large-scale/HPC work. The post notes that applicants do not need to already have both AI and hydrology expertise; strong fundamentals and enthusiasm for interdisciplinary research are valued.
To apply, email [email protected] with the subject line format given in the post and include a CV, unofficial transcripts, a brief description of research experience and interests, areas of interest, and publications/code/GitHub if available. Applications are reviewed on a rolling basis, and Spring 2027 applicants are encouraged to apply early.
Funding details
Two PhD openings are advertised for Spring 2027 and Fall 2027. The post does not specify stipend, tuition coverage, or whether the positions are fully funded.
What's required
Applicants should have interest or background in hydro, water resources, atmospheric science, environmental science, civil engineering, remote sensing/GIS, geoscience, computer science/data science, or applied math. Desired skills include Python/scientific computing, machine learning/deep learning, hydrologic or atmospheric modeling, remote sensing, and large-scale/HPC experience. The post notes that applicants do not need both AI and hydrology backgrounds, but strong fundamentals and enthusiasm for interdisciplinary research are valued.
How to apply
Email [email protected] with the subject line format provided in the post. Include a CV, unofficial transcripts, a brief summary of research experience and interests, areas of interest, and publications/code/GitHub if available. The post says applications are reviewed on a rolling basis and Spring 2027 applicants are encouraged to apply as early as possible.
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