MSc Autonomy Technologies

This program combines electrical engineering, mechatronics, computer science and artificial intelligence to train students in the design and integration of autonomous systems. Coursework and projects build both a broad understanding of hardware and software components and a system-level perspective, so you learn how sensors, perception, planning, control, networking and human–machine interfaces work together in real-world autonomous solutions. Instruction is delivered in English, making the course accessible to international students.

You can focus on one of four advanced specialisations—Human‑System Interfaces, Networking & Collaboration, Planning & Control, and Sensing & Perception—while developing practical engineering skills that prepare you for interdisciplinary work. Graduates leave as competent engineers ready to enter fast-growing areas such as automotive, automation and robotics, communication services, or industrial services, where expertise in autonomous systems is in high demand.

Admission & applicant profile (concise)

• Typically hold a completed Bachelor's degree in engineering, computer science, mechatronics or a closely related field
• Solid foundations in mathematics, programming and basic electrical/mechatronic concepts are expected
• Proficiency in English (programme language is English)
• Interest in interdisciplinary, systems-oriented work combining hardware, software and AI

Curriculum overview

This research-focused MSc gives you advanced theoretical and practical tools to develop autonomous systems. The programme centers on the design and implementation of autonomy technologies, preparing students to address one of today’s most important engineering challenges through a mix of compulsory and elective coursework, hands-on labs, and scholarly work.

Students build their profile by taking required and optional modules in two of four specialisation areas: Human‑System Interfaces, Networking & Collaboration, Planning & Control, and Sensing & Perception. In addition to core classes, the curriculum includes elective seminars and lab courses that translate theory into practice. Practical and interpersonal skills are reinforced through a team project or an industry internship, and the degree is concluded with a research-driven Master’s thesis.

Learning outcomes

• Develop and evaluate autonomous systems by applying methods from sensing/perception, planning/control, networking, and human–system interaction.
• Carry out research and advanced design work, and produce a substantive Master’s thesis that demonstrates independent problem solving.
• Gain hands-on engineering experience through lab courses and a team project or industrial placement, and strengthen communication and teamwork skills for interdisciplinary collaboration.

Curriculum requirements (concise)

• Complete mandatory core modules.
• Choose and complete mandatory and elective modules in two of the four specialisation areas: Human‑System Interfaces; Networking & Collaboration; Planning & Control; Sensing & Perception.
• Take elective seminars and lab courses for applied experience.
• Participate in a team project or complete an internship to develop soft skills and industry-relevant practice.
• Submit and defend a research-oriented Master’s thesis.

Graduates are prepared for engineering roles in the rapidly growing field of autonomous systems across sectors such as automotive, automation and robotics, communication services, and industrial services. Typical positions include systems engineer for autonomous platforms, perception/planning/control engineer, robotics developer, and roles in sensor and network integration.

The programme’s blend of hardware and software education, practical lab work and industry internships also provides a solid foundation for research careers or continued academic study (PhD). Employers value the programme’s system‑oriented approach and specialisation options for tackling complex autonomy challenges.