University of Michigan

What you'll study

The programme covers core topics in systems modelling, optimisation and stochastic analysis combined with application-oriented electives. Core subject areas typically include optimisation and mathematical programming, stochastic processes and queuing theory, simulation modelling, statistics for engineering, production and operations systems, and human factors/ergonomics.

Students usually follow one of several pathways: a coursework-focused master’s with a practicum or capstone project, or a thesis-based research route under the supervision of a faculty member. Typical modules and course themes you can expect are:

• Deterministic and stochastic optimisation – linear, integer and nonlinear programming; network flows; Markov decision processes.
• Simulation and modelling – discrete-event simulation, model validation, simulation for manufacturing and service systems.
• Data analytics and machine learning – statistical learning, regression and classification methods, time-series analysis and predictive modelling for operations.
• Supply chain and production systems – inventory theory, production planning, logistics, scheduling and lean manufacturing principles.
• Quality, reliability and human factors – reliability engineering, Six Sigma concepts, ergonomics, safety and human-system interaction.
• Advanced electives and interdisciplinary options – topics such as healthcare systems engineering, smart manufacturing, cybersecurity for cyber-physical systems and entrepreneurship through collaborative institutes and centres.

Hands-on learning is emphasised through laboratory courses, case studies, industry-sponsored capstones and opportunities to work with research centres within the College of Engineering and across campus. Computational coursework makes use of standard optimisation, simulation and data-science toolchains.

Entry requirements

Applicants are expected to hold a bachelor’s degree in engineering, mathematics, computer science, or a closely related quantitative discipline. Typical academic preparation includes calculus, linear algebra, probability and statistics, and some programming experience.

Standard application materials include official transcripts, a statement of purpose describing academic and professional goals, letters of recommendation, and a CV or résumé. Applicants whose first language is not English will need to demonstrate English proficiency through an accepted test or equivalent evidence. Some applicants with non‑traditional backgrounds may be asked to complete prerequisite coursework before or during the programme.

Career prospects

Graduates enter a broad range of sectors where system-level thinking and quantitative decision-making are valued. Common career paths include roles as industrial engineers, operations research analysts, supply chain and logistics managers, process improvement engineers, quality and reliability engineers, and data scientists focused on operational problems.

Employers span manufacturing, automotive and mobility companies, healthcare systems, logistics and distribution firms, consulting companies, technology firms, and governmental agencies. Alumni also pursue doctoral study or transition into product management and entrepreneurial ventures that combine engineering and business skills.

Why study at University of Michigan

The University of Michigan offers an industrial engineering programme embedded in a large, research-intensive engineering school with strong connections to industry and interdisciplinary centres. Students benefit from access to specialised research labs, established partnerships with manufacturing and healthcare organisations, and experiential learning opportunities such as industry capstones and internships.

Ann Arbor’s vibrant technology and engineering ecosystem, proximity to major manufacturing and mobility clusters, and an extensive alumni network support professional development and recruitment. Faculty research spans optimisation, human factors, supply chains, healthcare engineering and data-driven operations, providing students with access to contemporary problems and applied research projects.