Assistant​/Associate​/Full Professor Optimization and Statistics

Assistant/Associate/Full Professor Optimization and Statistics Special Instructions for More Details

Interested applicants should electronically submit a cover letter (candidates must clearly indicate if they are seeking the Optimization or Statistics position and the faculty rank for which they are applying), curriculum vitae, separate statements of research and teaching, and the names and contact information of three references. Applications will be evaluated beginning on December 12, 2025 and continue until a successful candidate has been identified.

The intended start date is August 16, 2026.

Job Title:

Assistant/Associate/Full Professor – Optimization and Statistics

Posting Number: P2233F

The Auburn University Department of Industrial & Systems Engineering (ISE) invites applications for two open‑rank tenure‑track faculty positions at the Assistant, Associate or Full Professor level. Candidates should select one of the following two positions:

• Optimisation
  :
  Candidates applying to this position must have strong theoretical foundations in optimisation with a focus on real applications. The department desires those who have experience with leveraging machine learning and artificial intelligence methods for optimisation. Specific research areas may include deterministic optimisation (integer, nonlinear, combinatorial), global and non‑convex optimisation, machine learning for optimisation, explainable AI, heuristic and meta‑heuristic approaches, network design and analysis, and other related topics in optimisation, modelling and decision sciences.
• Statistics
  :
  Candidates interested in this position must have solid foundations in statistics, with preference given to those with a strong basis in process control, reliability, Six‑Sigma (Black Belt or Master Black Belt preferred), the theory of machine learning, and artificial intelligence. Specific research areas include classical, Bayesian, and/or non‑parametric statistics; information science, data mining, or data analytics; statistical process control; machine learning methods (supervised and unsupervised learning, deep learning, reinforcement learning, etc.);
  
  artificial intelligence methods (predictive modelling, natural language processing, generative AI); risk analysis, real options and finance; and other related topics in statistics.

Salary range begins at $100,000, with flexibility based on experience and qualifications. The ISE Department at Auburn University has a strong research program and a long tradition of excellence in both graduate and undergraduate education.

Eligible candidates must hold an earned doctorate in Industrial and Systems Engineering or a closely related discipline at the time of employment. Candidates should demonstrate potential for high‑quality research and teaching, and excellent interpersonal and communication skills. For associate or full professor level applicants, a commensurate record of extramurally funded research, top‑tier scholarly publications, successful extramural collaborations, and excellence in teaching will be required.

Faculty rank and salary will be commensurate with experience and qualifications. Candidates must be able to meet eligibility requirements to work in the United States at the time of employment and continue working legally for the proposed term of employment.

Successful candidates will be expected to establish a robust extramurally funded research program and to teach undergraduate and graduate courses in one or both fields listed above. They will also be expected to collaborate with ISE faculty on research with applications in manufacturing, logistics, transportation, human factors, healthcare, and systems engineering; mentor undergraduate and graduate students; participate in outreach; and provide service to the department, college, and university.

It is our policy to provide equal employment and education opportunities for all individuals without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, gender expression, pregnancy, age, disability, protected veteran status, genetic information, or any other classification protected by applicable law. Please visit our website to learn more.