Master's in Industrial Informatics

Overview

Industry is rapidly changing toward customised production and a digitalised economy. Central to this shift are Cyber‑Physical Systems (CPS): integrated, intelligent systems that tightly combine hardware and software to sense, compute and actuate on the physical world in real time. CPS typically span many spatial and temporal scales, rely on highly networked communications, and expose digitalised functions and data as services over the Internet (think Internet-of-Things and Internet-of-Services).

Why this specialisation matters

Industrial Cyber‑Physical Systems (ICPS) are the digitally represented, networked infrastructures that underpin modern industrial operations—from product and process engineering through supply chains. Their competitive value depends on the ability to collect, analyse and act on large, heterogeneous data streams so that industrial plants and enterprises can be managed, supervised and operated efficiently and reliably. ICPS must also interact with enterprise IT and other real-time systems across business processes, making effective information-driven integration essential for contemporary industry.

What you will study and where it applies

Bridging computing, control, mechatronics, communications and software engineering, this specialisation examines the technical and methodological challenges of building, integrating and operating CPS ecosystems. It prepares graduates to address problems across a wide range of domains where CPS principles are penetrating practice—energy, healthcare, manufacturing, transportation, robotics, smart cities, defence and consumer/enterprise applications.

Typical expectations for applicants

• Programme language: English.
• Interest in cyber‑physical systems, industrial automation, IoT, and data‑driven engineering.
• Relevant foundational knowledge in areas such as electrical engineering, control systems, computer science, software engineering or mechatronics is advantageous.
• Be prepared to work with complex, heterogeneous data sources and real‑time networked systems.
• International applicants should review the university’s official admission criteria and language requirements for exact documentation and eligibility details.

Curriculum overview The master’s curriculum spans three semesters and totals 90 credit points (CP). The taught part is spread across two semesters (summer and winter), each running about six months, and culminates in a research-focused third semester dedicated to a 30 CP master's thesis. Courses combine lectures, practical laboratory sessions and project work to ensure both theoretical grounding and hands‑on experience.

Key modules and learning outcomes The first (summer) semester focuses on Industrial Cyber‑Physical Systems (5 CP), Digitalisation Engineering (5 CP) and Industrial Internet of Things (5 CP), supported by a 10 CP group project that fosters collaborative system development. An elective (5 CP) — for example Innovation Engineering — allows you to tailor learning toward creativity and technology management. In the second (winter) semester you study Robotic Systems (5 CP), Mathematical Modelling of ICPS (5 CP) and Data Science and Analytics (5 CP), alongside a 10 CP peer project that emphasises teamwork and cross‑disciplinary integration. A second 5 CP elective (e.g., Human Factors and Augmented Reality) offers further specialisation.

Learning outcomes include the ability to design and engineer industrial cyber‑physical systems, apply IIoT architectures and digitalisation methods, model and analyse dynamic systems mathematically, and extract actionable insights with data science techniques. The project components develop teamwork, system integration and practical laboratory skills, while the thesis semester trains you in independent research and in presenting a substantial engineering solution or study.

Program structure and requirements (concise)

• Summer semester (March–August): Industrial Cyber‑Physical Systems (5 CP), Digitalisation Engineering (5 CP), Industrial Internet of Things (5 CP), Group Project (10 CP), Elective 1 (5 CP; e.g., Innovation Engineering).
• Winter semester (September–February): Robotic Systems (5 CP), Mathematical Modelling of ICPS (5 CP), Data Science and Analytics (5 CP), Peer Project (10 CP), Elective 2 (5 CP; e.g., Human Factors and Augmented Reality).
• Third semester: Master’s thesis (30 CP).
• Total: 90 CP.
• Course formats: lectures, projects and laboratory work.
• For further details on course rationale and organisation, a programme overview video is available.

Graduates are prepared for technical and interdisciplinary roles that bridge hardware, software and data in industrial settings. Typical positions include ICPS/IoT engineer, automation and control systems engineer, robotics and mechatronics developer, data‑analytics engineer for industrial applications, and systems architect for smart manufacturing and supply‑chain solutions.

The programme's emphasis on real‑time systems, networked control, data analytics and industry‑linked projects also equips alumni for R&D roles, consultancy and technical management in sectors such as manufacturing, energy, healthcare, transportation, robotics and smart cities — as well as for continuing to doctoral studies.