Open Positions

Faculty Positions 

Tenure-track/Tenured Faculty Positions in the Department of Statistics and Data Sciences

The Department of Statistics and Data Sciences (SDS) at The University of Texas at Austin invites applications for tenured or tenure-track faculty positions to begin in August 2026.  We welcome applicants at any rank with research interests in any area of statistics and data science, whether theoretical, computational, or application-driven. We strongly encourage applications from candidates who work in scientific machine learning, the mathematical and statistical foundations of machine learning, high-dimensional statistical theory, or AI for science, because multiple positions in these areas may be available through various college and university-level initiatives. 

Candidates should have a doctoral degree in statistics, biostatistics, computer science, machine learning, applied mathematics, or a related discipline by August 2026. Further details about the position and instructions for submitting an application are available here.

Applications will be reviewed on an ongoing basis, but priority will be given to applications received on or before November 13, 2025.

Tenure-track/Tenured Faculty Position -- Scientific Machine Learning and AI for Science in the Oden Institute for Computational Engineering and Sciences and the Department of Statistics and Data Sciences

The Oden Institute for Computational Engineering and Sciences and the Department of Statistics and Data Sciences at The University of Texas at Austin have an opening for a tenured or tenure-track faculty position beginning Fall 2026 in the area of Scientific Machine Learning and AI for Science. We are seeking candidates who address challenging scientific and technological problems through advances in statistical and mathematical AI and ML theory and algorithms. Examples of topics of interest include: statistically-principled methods for uncertainty quantification; operator learning and learned surrogates with clear statistical validation; Bayesian inverse problems and data assimilation via measure transport and amortized inference; robustness and distribution shift in scientific ML; causal inference for mechanistic systems; and sequential experimental design and control (including reinforcement learning) under uncertainty. These topics are meant as illustrations, and not as an exhaustive list. This search is being conducted jointly by the Oden Institute and the Department of Statistics and Data Sciences as part of a campus-wide commitment to expanding the development of AI for Science and Scientific Machine Learning at UT Austin. The successful candidate will have half of their teaching duties in the Oden Institute’s Computational Science, Engineering and Mathematics (CSEM) graduate program and half in the Department of Statistics and Data Sciences. This position is open to applicants at all ranks, with a preference for hiring at the assistant or associate professor level. 

Candidates must have a Ph.D. degree in computational science, statistics, data science, computer science, mathematics, engineering, or a related field by August 2026.  Further details about the position and instructions for submitting an application are available here.

Review of applications will begin November 15, 2025, and will continue until an appropriate candidate is identified.

Postdoctoral Fellowship Positions 

Postdoctoral fellows in the Department of Statistics and Data Sciences are recent graduates of Ph.D. programs who do research in statistics, data science and related fields under the mentorship of one or more of our faculty members. Typically, fellows are appointed for a period of 1-2 years.

• Postdoctoral fellowship in Data Science with Professor Roger Peng. This position provides candidates with the opportunity to conduct research in the theory of data analytic practice and to expand the training of data analysis to large audiences. Qualifications: PhD in statistics, biostatistics, computer science, genomics, bioinformatics, or related data intensive field; experience teaching hands-on data analysis skills in R required. Applications will be accepted until the position is filled.  Applicants should submit (1) a cover letter including a brief description of an experience teaching data analysis or any other relevant curriculum; (2) a CV and; (3) a link to their GitHub profile, if available, to roger.peng@austin.utexas.edu. Further details about this position can be found here.
• The NSF-Simons AI Institute for Cosmic Origins (CosmicAI) invites applications for two Postdoctoral Fellow positions in Artificial Intelligence (AI) for scientific discovery. Each position offers an opportunity to contribute to the development of foundational AI methodologies and their application to data-intensive challenges in astronomy and physics. The Institute’s overarching goal is to create transparent, interpretable, and scientifically grounded AI systems that enable robust inference, accelerate discovery, and deepen our understanding of the Universe. These positions focus on developing methods that are explainable, trustworthy, and aligned with scientific reasoning. The Fellows will join an interdisciplinary community advancing research in symbolic reasoning, explainable and interpretable AI, optimization, Bayesian inference, and experimental design, all in the context of complex scientific data. Further details about these two positions, including qualifications and application instructions, can be found here.
  • The fellow selected for the first position, Theoretical and Methodological Advances, will work closely with Professor Alessandro Rinaldo and Assistant Professor Arya Farahi. The application deadline is January 10, 2026.
  • The fellow selected for the second position, Model Development and Data Analysis, will work closely with ssistant Professor Arya Farahi. The application deadline is December 5, 2025.

Graduate Student Positions 

Teaching Assistant 

The Department of Statistics and Data Sciences regularly hires The University of Texas at Austin graduate students to serve as teaching assistants for our undergraduate courses. Applicants for these positions should have a strong background in statistics and/or data science. 

• To apply for a Teaching Assistant position, please fill out this survey.

Undergraduate Student Positions

Undergraduate Course Assistants

The Department of Statistics and Data Sciences regularly hires The University of Texas at Austin undergraduate students who have completed specific courses to serve as an undergraduate teaching assistant for the course.  In addition, the department employs undergraduate student assistants to support the main office operations.

• There are no open positions at this time.