Computer Engineering

Overview

This Master's programme addresses the architecture, design, implementation, evaluation and operation of computer, communication and embedded systems, with a strong emphasis on hardware and system-level software. Depending on system requirements, functions and algorithms may be realised as software on general-purpose architectures, as dedicated digital hardware, or as hybrid hardware–software solutions. The course therefore combines hands-on engineering with theoretical foundations across multiple layers of computing systems.

Graduates are prepared for demanding roles in industry, business and research, gaining high professional mobility within the fast-evolving field of computer engineering. The curriculum focuses on digital hardware, systems theory, systems-related software and algorithmic methods, while training students in a scientific approach to problem solving. Project work and team-based activities are integral, and there is an option to develop entrepreneurial skills for those interested in start-ups.

This programme is unique among the German TU9 universities in bringing together four core focal areas: digital computer hardware, system-related software, algorithms and information & communication technology. Students learn to integrate, analyse and evaluate the full stack of system components. RWTH’s interdisciplinary environment offers abundant opportunities to engage with both application-driven and foundational research; final theses and elective choices can concentrate on emerging technologies such as neuromorphic hardware and quantum information technology, or explore neighbouring disciplines.

Recommended background and admissions expectations

• Solid undergraduate foundation in electrical engineering, computer engineering, computer science or a closely related field (demonstrated knowledge in digital hardware, systems theory, software and algorithms).
• Ability and willingness to work in teams and on applied projects; experience with project-based coursework is advantageous.
• Interest in scientific problem solving and in integrating hardware and software solutions.
• Optional: interest in entrepreneurship/start-up development for those wanting to pursue related modules or activities.
• Language of instruction: English (proof of English proficiency is required—refer to the official programme page for specific documentation and minimum levels).

For exact formal admission criteria, required documents, application deadlines and English-language proof, consult the programme’s official admission information.

Structure and focus (overview)

This full‑time Master’s programme runs over four semesters (two years), including the preparation and defence of the Master’s thesis. You may begin the programme in either the winter or the summer semester. The taught curriculum is built from a mix of compulsory and compulsory‑elective modules that define the programme’s technical profile and are supported by an extensive offer of laboratory courses, project work and seminars. In addition, students can choose from a broad range of elective courses across the university—covering technical subjects, economics, soft skills and languages—to shape their individual study plan.

Core components and academic experience

The programme is organised into several parallel module catalogues: CORE (in‑depth foundational lectures), ELECTIVE (application‑oriented Master’s lectures), GENERAL (Master’s courses from related subject areas), and ADDITIONAL (interdisciplinary qualifications). All students complete practical learning through at least one laboratory or project and one seminar, and undertake either a large group project or an alternative industrial placement accompanied by a lecture. A compulsory “Scientific Integrity” module ensures familiarity with ethical standards in research. If you cannot demonstrate German at level B1, German language courses are mandatory. The Master’s thesis is an independent, predefined research project completed over a fixed six‑month period and concluded with an oral presentation and defence. A visual breakdown of credit‑point requirements per area is provided in the programme materials.

Study flexibility and suggested profiles

There are no fixed specialisations; instead the programme gives you freedom to select modules that match your interests and career goals. To help with planning, suggested study profiles present meaningful module combinations—examples include Digital Hardware Engineering; Data Sensing and Processing; Machine Learning and Artificial Intelligence Systems; Digital Energy Systems; Autonomous and Cyber‑Physical Systems; and Systems for Human‑Machine Interaction. These profiles are illustrative only and may be updated over time; you may assemble other combinations under the programme’s general framework.

Key modules and expected learning outcomes

• Key modules: in‑depth core lectures, application‑oriented electives, interdisciplinary general courses, practical laboratory and project modules, seminars, and the six‑month Master’s thesis.
• Practical outcomes: advanced hands‑on skills from laboratory and project work; ability to design, implement and evaluate complex hardware/software systems; experience with industrial practice or large team projects.
• Research and professional outcomes: independent scientific research competence demonstrated in the Master’s thesis plus ethical awareness through the Scientific Integrity module; improved communication, economics and language skills via elective offerings.

Concise programme requirements

• Full‑time duration: 4 semesters (2 years); programme may start in either semester.
• Module mix: compulsory and compulsory‑elective modules, plus a wide choice of electives across the university.
• Practical work: at least one laboratory or project module and one seminar; large project group or industrial practice plus accompanying lecture.
• Scientific Integrity: completion of required ethics module.
• Language: German courses mandatory for students without certified B1 level.
• Master’s thesis: predefined independent project, fixed duration of six months, finished with an oral presentation and defence.
• Study planning: freedom to choose modules; non‑binding suggested study profiles available to guide selection.
• Credit‑point distribution: visual overview available in the programme materials showing required credit points by subject area.

Graduates are prepared for technical and leadership roles in development departments across industry and business, particularly in embedded systems, digital hardware design, systems software, algorithm and AI systems, and communication technology. The programme’s mix of hardware and software focus, mandatory internship or large project experience, and elective specialisations supports direct entry into R&D, product development, systems integration, and engineering roles.

The degree also provides a strong foundation for academic careers and doctoral studies, as well as entrepreneurial paths (start-ups) owing to training in scientific methods, interdisciplinary electives, and exposure to cutting-edge technologies. High professional mobility is emphasised, enabling graduates to work in both industry and research environments domestically and internationally.