Assistant, Associate, Full Professor (Tenured/Tenure-Track) in Foundational AI/ML

We invite applications for faculty positions of all ranks (tenure-track assistant, tenured associate and full professors) as part of a cluster hire in foundational artificial intelligence (AI) and data science with core applications in the life sciences. This cluster hire is part of The University of Texas at Austin's Cluster Hiring Program in AI and Data Analytics (AI DA). Outstanding candidates who work in the foundations of AI and machine learning will be considered. Research topics include developing novel tools in generative AI, advancing algorithmic and statistical methods for training and inference, and enhancing the robustness and interpretability of machine learning models, among other areas. Applicants' work should have the potential to impact AI models with core applications in the life sciences. These applications include (but are not limited to) (1) deep learning and biologics, especially protein engineering and design; (2) the use of major computational tools for biochemistry such as AlphaFold; (3) advancing the state of the art in use-cases for AI and health such as imaging, video, and representation learning through large-scale language models (LLMs) or other large-scale models; (4) the use of AI to improve decisions around personalized medicine, disease diagnosis, or the acceleration of drug discovery and development.

It is broadly expected that successful candidates will likely be placed in the departments of Computer Science, Statistics and Data Sciences, Electrical and Computer Engineering (ECE), Operations Research, or Mechanical Engineering within the College of Natural Sciences and the Cockrell School of Engineering.

Faculty will collaborate with numerous researchers involved in UT-Austin's Machine Learning Lab, Texas Robotics, Institute for the Foundations of Machine Learning (IFML), and Good Systems initiative as well as the newly launched Center for Generative AI and its associated GPU cluster consisting of 600 GH200 nodes.

All positions are subject to the availability of funding. Austin, the capital of Texas, is a center for the high-tech industry, including companies such as Amazon, AMD, Apple, Applied Materials, AT&T, Dell, Google, IBM, National Instruments, and Samsung.

All tenure-track positions require a Ph.D. or equivalent degree in Computer Science, ECE, Statistics and Data Science, Operations Research, or a related area at the time of employment. Successful candidates are expected to pursue an active research program, to teach both graduate and undergraduate courses, and to supervise graduate students in research.

All faculty positions require a cover letter, current curriculum vita, research statement, teaching statement and selected publications. For all positions, at least three (3) reference letters are required. Review of applications will begin on December 1, 2024, with an application deadline of December 16, 2024. Applications received after the deadline are not guaranteed full consideration.

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.