RESA I - TExUS

The University of Texas at Austin•Austin, UT

17d•Onsite

About The Position

The "University of Texas Extreme Weather and Urban Sustainability” (TExUS) lab located in the Jackson School of Geosciences at the University of Texas-Austin is a multidisciplinary research collective led by PI Professor Dev Niyogi. Working with us will give you the opportunity to explore open-ended research in a resource-rich, collaborative environment. We are seeking a highly motivated individual with a demonstrated capacity to conduct independent research , specifically on problems related to AI and geoscience, for a 5-8 month Co-op in-person in Austin, TX, beginning February 2026, or as soon as possible thereafter. We are driven to produce high-impact research with real-world applications. As a research scientist at TExUS, you will support our core mission working side-by-side with PhD students, postdocs, and municipal partners to advance artificial intelligence for geoscience. Your role will be flexible and largely self-determined. Essential responsibilities may include developing, testing, and deploying code for large-scale model training and inference, attending weekly group meetings, and leading independent research efforts. Ideal candidates will possess a blend of engineering, analytical, and interpersonal skills to effectively collaborate with our partners. This is a one year temporary full-time salaried position with benefits, including healthcare, vision and dental coverage. There is a possibility of renewal for up to an additional 12 months contingent on performance. Hired persons are expected to be available in-person during standard business hours (M-F; 9AM-5PM).

Requirements

Bachelor's degree.
Basic engineering and/or scientific equipment ordinarily used in college laboratory work .
Currently authorized to work in the United States
Relevant education and experience may be substituted as appropriate.

Nice To Haves

Postgraduate degree (Masters, Ph.D.) awarded by a major accredited university in a computational discipline (e.g., Computer Science, Electrical Engineering)
Research experience: demonstrated capacity to conduct university-level research
Publications accepted to top AI venues (e.g., ICML, ICLR, NeurIPS)
Strong math and code abilities
Proficiency in Python, modern ML frameworks (e.g., PyTorch, JAX/FLAX)
Software engineering (SWE) experience, preferably as part of a large/industrial team
Familiarity with atmospheric/Earth/geological sciences

Responsibilities

In-person availability 40 hrs/week (Mon-Fri; 9AM-5PM)
Effective, cordial collaboration with group PhD students, postdocs, and partners
Successful completion (i.e., completed manuscripts) of 2-3 research projects submitted to high impact AI venues (ICLR, ICML, CVPR) or top-flight Journals (Nature)