Tenured or Tenure-Track Faculty Position, Fall 2025 - Computational Mathematics - UT Austin

The Oden Institute for Computational Engineering and Sciences and the Department of Mathematics at The University of Texas at Austin have an opening for a tenured or tenure-track faculty position beginning Fall 2025 in the area of Computational Mathematics. We are seeking candidates working on the mathematical and algorithmic foundations of Scientific Machine Learning in a broad sense. Particular areas of interest include, but are not limited to, development and analysis of machine learning models for scientific computing, theory and algorithms for sampling, techniques for high-dimensional problems, inverse problems, multiscale modeling and nonlinear dynamics. We are also interested in the development and analysis of large-scale nonconvex optimization methods used in machine learning. The ideal candidate will bring mathematics and computation together, and have a track record of engaging with applications. This search is conducted jointly between the Oden Institute and the Department of Mathematics as one of several faculty lines committed 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 graduate program and half in the Department of Mathematics. This position is open to applicants at all ranks: assistant, associate, and full professor, including the possibility of appointment as a chaired professor for candidates with exceptional qualifications. For more information about the Oden Institute for Computational Engineering and Sciences, please visit https://www.oden.utexas.edu. For more information on the Department of Mathematics, please visit https://math.utexas.edu.

Candidates must have a Ph.D. degree in Mathematics or a closely related field. In addition to the ability to teach mathematics at the undergraduate and graduate levels, the successful candidate must be qualified to teach graduate classes associated with the Computational Science, Engineering and Mathematics program at the Oden Institute. The successful candidate will be expected to create undergraduate and graduate learning environments that address the needs of students from a variety of backgrounds, with differing learning styles and abilities. Further, the successful applicant will be expected to develop an externally sponsored research program, mentor graduate students, collaborate with other faculty, and be involved in service to the university and profession.

Interested applicants should submit the following materials: (1) a cover letter, (2) curriculum vitae, (3) research statement (max 4 pages), (4) teaching statement (max 2 pages), and (5) either a minimum of three letters of reference (candidates for an assistant or associate professor position) or the names of three references (candidates for a full professor position). Candidates should address their submission to the Computational Mathematics Faculty Search Committee. Review of applications will begin November 15, 2024, and will continue until an appropriate candidate is identified. We anticipate virtual interviews in December and in-person campus interviews in the first couple of months of 2025.

The successful candidate will be required to complete an Employment Eligibility Verification form and provide documents to verify identity and eligibility to work in the USA. A security sensitive background check will be conducted on the applicant selected.

Please address questions to Prof. Gunnar Martinsson, the Computational Mathematics Faculty Search Committee Chair (pgm@oden.utexas.edu). ** For application questions, contact Ruth Park (ruth.park@oden.utexas.edu).

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.