The Department of Mathematics and Statistics at Utah State University (USU) invites applications for a 9-month tenure-track Assistant Professor position in the Mathematics of Artificial Intelligence, with a starting date of August 1, 2026. We seek candidates whose research bridges mathematical foundations and computational methods to advance AI methodology and applications. This position is inherently interdisciplinary. We seek candidates who demonstrate potential for strong synergies with the department's existing research strengths in Applied/MathBio, Statistics and Machine Learning, Analysis/PDE, and Discrete Math. Candidates should also be able to partner broadly with researchers across campus such as those in the Data Science and Artificial Intelligence Center, School of Computing, engineering, natural sciences, agriculture, natural resources, and social sciences. Ideal candidates will have a robust mathematical background and have expertise in one or more of the following areas (not exhaustive): Uncertainty quantification, stochastic analysis, or probabilistic modeling; Statistical learning theory, high dimensional inference, or generalization/robustness; PDEs, dynamical systems, or stochastic differential equations especially as they interact with learning; Graph and network methods, algorithmic combinatorics, discrete optimization, or network science; Principled methods for interpretability, certification, fairness, or robustness in AI. Ideal candidates should also show interest in principled quantitative approaches to large-scale data from genetics, networks, or environmental systems. Preference will be given to applicants with potential to (a) attract external funding (e.g. NSF, NIH, DOE, DoD, etc.), (b) engage in multi-investigator or cross-unit proposals, (c) foster collaborations with industry, government labs, or domain scientists, and (d) contribute strongly to national or international programs in trustworthy and foundational AI.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
Job Type
Full-time
Career Level
Entry Level
Industry
Educational Services
Education Level
Ph.D. or professional degree