University of Virginia

What you'll study

This programme combines core systems engineering methods with human factors, cognitive systems engineering and intelligent systems techniques. You will study how to specify, model and validate complex systems that include people, software and hardware components, and how to design interfaces and decision support that improve safety, performance and user experience.

• Core systems engineering: systems lifecycle, requirements engineering, model-based systems engineering and systems architecture.
• Human-centred topics: human factors, cognitive engineering, human–computer interaction, usability and experimental methods for evaluating human performance.
• Intelligent systems and autonomy: machine learning for systems, decision systems, human–autonomy teaming, perception and sensor integration.
• Supporting methods: data analytics, probabilistic modelling, control systems, verification and validation, and systems safety and resilience.
• Design and project work: individual or team capstone project or thesis emphasising applied design, prototyping and evaluation in domains such as healthcare, transportation, defence or consumer technology.

Structure

The programme is taught through a mixture of lectures, laboratory sessions and project work. Students typically complete a combination of required core courses and electives, culminating in a substantial applied project or thesis that integrates human systems and intelligent systems approaches. Interdisciplinary collaboration with computer science, psychology and industry partners is a central feature.

Entry requirements

Applicants should hold a good bachelor’s degree in engineering, computer science, applied mathematics, psychology with quantitative emphasis, or another closely related discipline. Typical application materials include academic transcripts, a personal statement describing relevant experience and interests, a curriculum vitae, and references. Where English is not a first language, an approved English language qualification is required. Prior coursework or experience in programming, statistics or basic systems concepts is advantageous. Admissions committees consider professional experience and research potential when assessing candidates.

Career prospects

Graduates are prepared for roles that bridge engineering, human factors and intelligent systems. Common career paths include systems engineer, human factors or usability engineer, human–machine interaction designer, autonomy engineer, data scientist for socio-technical systems, product manager or consultant. Employers span industries such as aerospace and defence, automotive and autonomous vehicles, healthcare and medical devices, transportation and logistics, consumer technology and government research labs. Graduates also move into research roles or continue to PhD study in systems engineering, human factors or related fields.

Why study at University of Virginia

The University of Virginia offers this programme within a research-led engineering school that emphasises interdisciplinary collaboration and applied problem solving. Students benefit from access to laboratories and research groups working on cyber-physical systems, autonomy and human-centred design, as well as opportunities to work with faculty whose expertise spans engineering, computer science and behavioural science. The university’s industry links, regional technology ecosystem and career services support applied projects, internships and job placement. The programme’s balance of rigorous systems methods and human-centred intelligent systems prepares graduates to design safer, more effective technologies in complex real-world settings.