Hyeong Suk Na

A fully funded PhD position is available in the Department of Industrial and Systems Engineering at the University of Missouri, supervised by Assistant Professor Hyeong Suk Na. The research focus is on large-scale stochastic optimization or agent-based simulation, with applications in industrial engineering and related fields. The position offers a combination of research and teaching assistantships, covering full tuition, a 12-month stipend, and benefits, with renewal possible based on performance. Applicants should hold an M.S. in Industrial and Systems Engineering, Operations Research, Computer Science/Engineering, Transportation Engineering, Statistics, Mathematics, or a related discipline. Required qualifications include experience in academic research writing and presentation, strong programming skills (CPLEX, GAMS, Gurobi, AMPL, Python, R, MATLAB, AnyLogic), and a solid understanding of stochastic optimization or simulation methods. Interested candidates should complete the online survey by December 1, 2025. The review of applications will begin immediately and continue until the position is filled. For more information, visit the department and program websites provided.

Two fully funded PhD Graduate Research Assistant positions are available in the Smart, Sustainable, and Resilient Systems (SSRS) Laboratory in the Department of Industrial and Systems Engineering at the University of Missouri (Mizzou). The openings are with Assistant Professor Hyeong Suk Na and begin as early as Spring 2027. The research areas are: (1) Large-Scale Stochastic Optimization using AI/ML and (2) Computer Vision/Image Processing. These topics connect strongly with Industrial Engineering, Operations Research, Computer Science, Statistics, Mathematics, and related quantitative fields. Funding includes full tuition support, a stipend, and benefits through graduate research/teaching assistantships. The appointments are expected to last 12 months, with renewal possible based on satisfactory academic and research performance. Preferred applicants should have an M.S. degree completed or expected before enrollment in Industrial and Systems Engineering, Operations Research, Computer Science or Engineering, Transportation Engineering, Statistics, Mathematics, or a closely related field. Strong quantitative, analytical, and programming skills are important, along with prior research experience such as an M.S. thesis, publication, research project, or similar scholarly work. Strong written and oral communication skills and the ability to work independently and collaboratively are also expected. For Position 1, experience or strong interest in mathematical optimization, stochastic modeling, simulation, and related computational methods is desirable, with tools such as Python, Gurobi, CPLEX, GAMS, AMPL, MATLAB, R, or AnyLogic. For Position 2, experience or strong interest in computer vision, image processing, deep learning, or geospatial analytics is desirable, with tools such as Python, PyTorch, TensorFlow, OpenCV, and GIS software. Interested students should submit materials through the preliminary review survey linked in the post. This is an initial screening step only and is not the official University of Missouri Graduate School application. Review begins immediately and continues until both positions are filled.