Seattle University

What you'll study

This programme combines core systems engineering principles with human-systems integration and intelligent systems topics. You can expect a mix of required core modules, concentration electives and a culminating applied project or thesis. Teaching emphasises model-based systems engineering, human-centred design, and practical evaluation of intelligent systems in real-world contexts.

• Core systems engineering – systems thinking, requirements engineering, systems architecture, verification and validation, systems lifecycle and risk management.
• Human systems engineering / human factors – human performance and limitations, cognitive systems engineering, ergonomic and user-centred design methods, usability evaluation and metrics.
• Intelligent systems – fundamentals of machine learning and AI as applied to system autonomy, decision support systems, human-AI interaction, explainability and trust in autonomous systems.
• Modeling and simulation – system modelling languages and tools, simulation for design space exploration, human-in-the-loop simulation and scenario-based testing.
• Data and analytics for systems – sensor data integration, analytics pipelines, system health monitoring and predictive maintenance approaches.
• Capstone / applied project or thesis – interdisciplinary team projects or individual research addressing a real-world systems integration challenge, often in collaboration with industry or campus research labs.

Lectures are reinforced with laboratory sessions, hands-on workshops and project-based learning. Students are encouraged to draw on electives from computer science, human-centred design, industrial and systems engineering, or robotics to tailor the programme to specific career goals.

Entry requirements

Applicants should hold a bachelor's degree from an accredited institution, typically in engineering, computer science, information systems, mathematics, cognitive science or a closely related technical field. Admissions expects evidence of quantitative background such as coursework in calculus, statistics and basic programming.

Other application components commonly include a curriculum vitae or résumé, academic transcripts, a personal statement outlining professional and academic goals, and letters of recommendation. Applicants with relevant professional experience but with non‑traditional academic backgrounds may be considered if they demonstrate sufficient technical preparation. International applicants must meet the university's English language proficiency requirements.

Career prospects

Graduates are prepared for roles that require integrating technical systems with human users and stakeholders. Typical job titles include systems engineer, human factors engineer, user experience engineer for complex systems, autonomy systems engineer, systems integration engineer, product manager for technical systems, and data-driven systems analyst.

Alumni find work across industries such as aerospace and defence, healthcare technology, automotive and mobility (including autonomous systems), robotics, industrial automation, and technology companies focused on intelligent platforms and services. The degree also provides a foundation for continuing to doctoral study in systems engineering, human factors, robotics or related research areas.

Why study at Seattle University

Seattle University offers this programme within a campus environment that emphasises applied, ethical and human-centred problem solving. The university’s location in the Seattle region gives students access to a dense technology ecosystem and potential industry partners in software, aerospace, healthcare and mobility.

Students benefit from small cohort sizes, faculty with interdisciplinary expertise in systems engineering, human factors and intelligent systems, and hands-on opportunities through labs and capstone collaborations. The programme’s focus on integrating technical rigour with human-centred design prepares graduates to build safer, more usable and more trustworthy complex systems.