University of Michigan

What you'll study

This master's pathway combines core systems engineering methods with specialised topics in human systems and intelligent technologies. Coursework typically covers systems architecture and integration, human factors and cognitive engineering, human–computer interaction, machine learning for decision support, sensor and perception systems, modelling and simulation of human behaviour, and system safety and reliability.

Instructional formats include lectures, small seminars, laboratory work and team-based design projects. Students normally complete a mix of required core courses and electives, and may choose between a research thesis or a project-based capstone that applies intelligent-systems methods to real-world human-centred challenges.

• Systems engineering fundamentals: requirements engineering, systems modelling, verification and validation
• Human factors and cognitive engineering: workload assessment, task analysis, human error modelling
• Intelligent systems: machine learning, probabilistic inference, decision support and autonomy
• Interaction and interface design: HCI methods, prototyping, usability testing
• Modelling & simulation: human-in-the-loop simulation, agent-based modelling
• Safety, resilience and ethics: risk analysis, trustworthy AI, socio-technical systems governance

Entry requirements

Applicants are expected to hold a bachelor’s degree in engineering, computer science, cognitive science, psychology with substantial quantitative coursework, mathematics, or a related discipline. Competitive candidates will demonstrate solid preparation in mathematics (calculus, linear algebra, probability/statistics) and programming; prior coursework or experience in systems engineering, human factors, HCI or machine learning is beneficial.

Typical application materials include academic transcripts, a statement of purpose describing relevant experience and goals, two or three letters of recommendation, and a curriculum vitae or résumé. International applicants must demonstrate English language proficiency where required. The programme considers the whole application package and values relevant professional experience, research background or portfolio work alongside academic records.

Career prospects

Graduates are prepared for roles that bridge technical system design and human-centred considerations. Common career paths include human factors engineer, systems engineer, interaction/UX researcher, intelligent systems engineer, autonomy/robotics engineer, usability specialist, and product manager for safety‑critical systems.

Alumni find work across industries such as healthcare technology, autonomous vehicles and transportation, aerospace and defence, consumer electronics, industrial automation, and consulting. The degree also provides a foundation for doctoral study in human factors, systems engineering, robotics or computer science.

Why study at University of Michigan

University of Michigan offers a multidisciplinary environment where engineering, computer science, cognitive science and design intersect. Students benefit from access to specialised research labs and centres that focus on robotics, human factors, transportation and healthcare technology, enabling hands-on experience with human-in-the-loop systems and real-world testbeds.

The College of Engineering connects students with industry partners, internship opportunities and an extensive alumni network. Faculty are active in applied and foundational research, providing mentorship for project‑based work and thesis research. Studying in Ann Arbor also offers a vibrant professional and academic community that supports collaboration across disciplines and career development.