Texas Tech University’s Department of Industrial, Manufacturing, and Systems Engineering (IMSE) is inviting applications for a PhD opening co-advised by Dr. Man Yiu (Tim) Tsang and Dr. Hamidreza Validi. The research focus is at the intersection of operations research, optimization, machine learning, and probabilistic modeling, with applications to large-scale, real-time systems. Key responsibilities include advanced data analytics on high-volume datasets, formulating robust decision models for stochastic environments, and evaluating the performance and risk profiles of complex systems.

Applicants should have a degree in Operations Research, Mathematics, Statistics, Industrial Engineering, or a related field. Required skills include strong analytical and critical thinking, experience with high-volume data, programming and/or optimization solvers, and effective communication in English. Preferred qualifications include training in mathematical programming, stochastic optimization, probability theory, statistical inference, and/or machine learning, as well as project experience in optimization under uncertainty, machine learning, and data analysis. Publications in peer-reviewed journals or conference proceedings are also valued.

The position is expected to start in Fall 2026. To apply, candidates should email Dr. Tsang and Dr. Validi with the subject line '[Fall 26 DSC Ph.D. Application] Your Name' and include a curriculum vitae, transcripts, a statement of purpose, and samples of recent publications or manuscripts. Review of applications will begin on March 27, 2026, and continue until the position is filled. Shortlisted candidates will be contacted for an interview.

This opportunity is ideal for students interested in operations research, stochastic optimization, robust optimization, machine learning, and data analytics, especially those seeking to work on real-world problems in finance, healthcare, and transportation. The IMSE department at Texas Tech University offers a collaborative research environment with access to cutting-edge resources and mentorship from leading faculty in the field.