University of Arizona

What you'll study

This programme builds from core engineering fundamentals toward specialised study of human-centred and intelligent systems. Early years emphasise mathematics, physics, programming and basic engineering analysis. Later years introduce systems modelling, control theory, probability and statistics, and optimisation methods.

• Human-systems topics: human factors and ergonomics, cognitive engineering, usability and user-centred design, workload and human performance assessment.
• Intelligent systems topics: machine learning and pattern recognition, sensor integration, autonomy and decision-support systems, perception and signal processing.
• Systems engineering foundations: requirements engineering, systems architecture, reliability and safety engineering, systems modelling and simulation, life-cycle analysis.
• Practical and professional skills: embedded systems and interfacing, software development for systems applications, data analytics, ethics in technology, project management and communication.
• Capstone and laboratory experience: team-based design projects that integrate human-centred design with intelligent components, laboratory exercises in human performance measurement and prototyping, and opportunities to work with interdisciplinary research groups or industry partners.

Students typically progress from foundational coursework to electives and a culminating senior design project that emphasises integration of people, processes and intelligent technology.

Entry requirements

Applicants are expected to hold a recognised secondary school qualification with strong preparation in mathematics (including pre-calculus or calculus) and science. Successful candidates typically demonstrate competency in algebra, calculus and basic physics; prior programming experience is strongly recommended.

• Competitive academic record in high school coursework, particularly in mathematics and sciences.
• Personal statement explaining interest in systems engineering and human-centred design; letters of recommendation are advantageous.
• Transfer applicants should present college-level coursework in calculus, differential equations or introductory engineering where available.
• International applicants must meet the University of Arizona's English language proficiency requirements.

Admission procedures follow the university's general undergraduate processes; applicants are encouraged to consult the university admissions pages for current application steps and supporting material guidance.

Career prospects

Graduates are prepared for roles at the intersection of people and intelligent technologies. Common career paths include:

• Human factors engineer / ergonomist working on product, cockpit or workplace design.
• Systems engineer responsible for integrating software, hardware and human interfaces in complex systems.
• Human–computer interaction (HCI) or user experience (UX) researcher and designer.
• Autonomy and robotics engineer focused on human-aware control and decision systems.
• Data scientist or machine learning engineer applying models to human-centred datasets.
• Roles in healthcare systems, transportation, aerospace, defence, automotive, consumer electronics and consulting, as well as further study at graduate level in systems engineering, human factors, cognitive science or AI.

Why study at University of Arizona

The University of Arizona offers this programme within a research-active engineering school with strong interdisciplinary links across cognitive science, computer science and biomedical engineering. Students benefit from hands-on laboratory courses, team-based capstone projects and opportunities to collaborate with faculty engaged in applied work on intelligent systems and human performance.

Located in Tucson, the university maintains partnerships with regional and national industry and research organisations in aerospace, defence, healthcare and technology, creating internship and employment pathways. The programme emphasises experiential learning, preparing graduates to design safe, effective and ethical systems that integrate people and intelligent technology.