This master's programme is organised around three principal tracks: Robotics (covering robotic systems of many types), Process Automation (with applications including biochemical systems), and Cognitive Systems (focusing on control strategies for collaborative systems). The curriculum builds on fundamental electrical engineering and control theory while offering pathways into more specialised, application-oriented topics.
Core instruction covers basic control theory and extends into advanced specialisations such as collaborative operation, real-time video and image processing, sophisticated communication between system components, and AI-driven control approaches. Students tailor their studies by choosing from a catalogue of electives that is regularly updated to reflect ongoing scientific developments, ensuring coursework remains current.
Participants have the freedom to design their profile by selecting electives that match their interests and career goals; the elective list is not fixed and will change periodically to keep the programme aligned with advances in the field.
Teaching combines lectures, tutorials and laboratory work with two substantial practical components: a team-based project group and an individual Master’s thesis. The project groups (typically formed by six or more students) and the thesis each concentrate on a single, up-to-date topic that reflects current technological and scientific advances. As you progress through the program, emphasis gradually shifts from classroom-based learning to hands-on, individual and team work.
Your first semester consists of mandatory classroom courses designed to bring students from diverse backgrounds to a common, solid level so everyone can succeed in the later elective offerings. After that foundation phase you select elective modules that determine your specialization—Robotics, Process Automation, or Cognitive Systems. You do not need to decide your specialization up front; choices are made as you move through the program. Electives commonly create links to specific institutes and research groups, which in turn propose topics for the project groups and MSc theses.
The curriculum covers a wide spectrum of technical challenges—electrical and electronic systems, advanced application scenarios across all three majors, programming and theoretical computer-science tasks, and mechanical problems—so almost any interest or career orientation can be pursued. Learning outcomes include a robust theoretical foundation, practical laboratory and software skills, collaborative project experience, and the capability to carry out independent, research-oriented MSc work that readies you for research roles or advanced industry positions.
Applicants must demonstrate solid mathematical ability and a strong grounding in computer systems to be eligible for this program. These competencies are treated as compulsory admission criteria.
Per the examination regulations (see §3), the university assesses these requirements solely by examining the number and content of relevant courses taken during your Bachelor’s degree. Evaluation is based on your BSc curriculum and official transcripts; the scope and count of academic classes in the relevant subject areas determine whether the requirement is met.
Any non-academic training (e.g., short courses, MOOCs) or professional work experience will not be considered for meeting these formal admission criteria. Only the coursework recorded in your undergraduate curriculum is used for this assessment.
Winter Semester (International)
15 May 2026
Graduates are prepared for technical and engineering roles in automation and robotics across industry sectors such as automotive, manufacturing, logistics, medical devices, biotech/process industries, energy, and industrial automation. Typical positions include robotics engineer, control systems engineer, automation/plant engineer, systems integrator, embedded/real-time software developer and AI/ML engineer for control applications. The curriculum’s mix of control theory, real-time processing and AI-based control targets employers seeking specialists in collaborative and autonomous systems.
The programme also provides a solid foundation for research careers and PhD study; the project group and individual master’s thesis offer applied and research-oriented experience attractive to R&D departments and research institutes. Graduates may also pursue roles in start-ups or consultancy services focused on smart manufacturing, Industry 4.0 and robotic automation solutions.
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