Position Description

Overview:

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 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.

Responsibilities:

• Research: develop an independent and externally funded research program at the interface of mathematics and AI.
• Teaching: deliver undergraduate core mathematics courses (1000-3000 levels), courses within the interdisciplinary/applied mathematics graduate core (see USU General Catalog at https://catalog.usu.edu/ and search courses with prefix MATH, numbered 5000+), and develop advanced courses in AI, machine learning, computational mathematics, and data science.
• Mentorship: supervise graduate students (PhD and MS, including the Industrial Math MS) and undergraduate students in programs including AI/data science and computational math.
• Collaboration: establish and maintain synergies across campus (e.g. computing, engineering, life sciences, natural resources, social sciences) and contribute to campus-level AI/data science initiatives.
• Service: departmental, college, and professional service consistent with expectations for a tenure-track faculty member.

The position is 50% research, 45% teaching and 5% service, with expectations that over time, the candidate will increase external funding, expand collaborative reach, and help build curricular strength in computational mathematics and data science.

Qualifications:

Minimum Qualifications

• Ph.D. in Applied Mathematics, Mathematics, Statistics, Computer Science, Engineering, or a closely related field.
• Research record of excellence at the interface of mathematics and AI/ML.
• Evidence of, or potential for, strong teaching and mentoring across diverse student populations.

Preferred Qualifications

• Experience in interdisciplinary collaboration, particularly with biological, ecological, and environmental scientists.
• Postdoctoral or equivalent training.
• Experience with external research funding and collaborative proposals.
• Evidence of, or potential for, collaborations with industry, government labs, or domain scientists.
• Evidence of, or potential for, contributions to national or international programs on trustworthy and foundational AI.

College/Department Highlights:

The Department of Mathematics and Statistics is committed to delivering advanced quantitative and analytic skills for professionals in education, industry, and research through classroom instruction as well as practical and research experiences. The Department is one of the largest departments at USU, with over 50 faculty members, 60 Master’s and PhD students, and 300 undergraduate majors. The College of Arts and Sciences and USU’s Research Office makes significant investments in faculty development, including startup packages, faculty seed grants, and proposal development assistance. 

USU is located in Logan, Utah, a city of 54,000-plus people in a picturesque mountain valley 1.5 hours north of Salt Lake City, and just minutes from the Cache National Forest. Its location puts us close to Utah’s vibrant tech economy, as well as recreation opportunities in Utah’s abundant national and state parks and monuments. Please see the department jobs website to view other available faculty and post-doc positions in the department.

Review of applications begins on December 15th, 2025, with the position open until filled.  For more information please contact search committee chair Dr. Luis Gordillo (luis.gordillo@usu.edu).

Required Documents:

Applicants should submit the following:

1. Cover letter addressing fit with the mission of this position and existing departmental strengths (upload in Candidate Profile under “Documents 1-5”)
2. Curriculum vitae (upload at the beginning of application in the Candidate Profile under “Resume/CV”)
3. Research statement (upload in Candidate Profile under “Documents 1-5”)
4. Teaching statement/philosophy (upload in Candidate Profile under “Documents 1-5”)
5. At least three letters of recommendation (to be submitted via MathJobs link below), with at least one addressing the applicant's teaching experience and potential

All application materials, except for reference letters, must be provided through the USU Jobs site: https://careers-usu.icims.com/jobs/9612/assistant-professor-in-the-mathematics-of-ai/job

Reference letters must be provided via MathJobs at www.mathjobs.org/jobs/list/27318.