This consecutive Master of Science trains you to design and manage digitally connected systems that are transforming modern industry. Building on the Industry 4.0 paradigm, the programme focuses on creating and linking virtual product and process models across the entire value chain — from planning and design through production to lifecycle monitoring — to speed development, improve quality, and optimise manufacturing. It is taught in English and aimed at preparing specialists who operate at the intersection of engineering and computer science.
The curriculum was jointly developed by the chairs of Engineering and Computer Science and Media, and emphasises flexible, interdisciplinary learning with a strong practical orientation. You will work with contemporary modelling concepts and tools for computer-aided modelling, simulation and visualisation, and deepen your understanding of information-theoretic approaches to data generation and handling. The programme actively links teaching and research: industry-defined research topics are introduced early and supervised in collaboration with partners, and students benefit from access to the Digital Bauhaus Lab — a state-of-the-art university research facility that supports experimental work and applied projects.
The course prepares you to represent, interpret, evaluate and optimise complex, cross-disciplinary processes in sectors such as construction, mechanical engineering and other industrial fields. Graduates leave with methodological skills to drive full digitalisation of design, manufacturing and application processes and with practical experience that is attractive to employers working on digital transformation initiatives.
This Master's programme combines lectures, tutorials, seminars, a supervised research project and a Master's thesis. It is designed as a full-time, four-semester course of study taught in English, leading to a Master of Science. The programme balances core foundations, engineering and computer-science methods, elective choices across departments, and substantial research practice to prepare you for advanced technical and interdisciplinary work in digital engineering.
Key modules and credits
Learning outcomes
Program requirements (concise)
For a full list of offered modules and the detailed module catalogue, see the programme curriculum page: https://www.uni-weimar.de/en/civil-and-environmental-engineering/studies/master-degree-programmes/digital-engineering/curriculum/
Admission overview
To be considered for this Master’s programme in Digital Engineering (Industrial Engineering), applicants should hold a relevant Bachelor of Science degree or an equivalent qualification approved by the programme’s examination committee. The programme expects supporting documents that demonstrate both academic suitability and sufficient English language ability.
Application materials
You must submit a one-page motivation letter written in English plus a self-written academic document. In addition, you need to provide proof of English language skills at the B2 level. For questions about what counts as an equivalent undergraduate degree, the precise format of the academic document, or which language certificates are accepted, consult the examination committee or the programme’s application information.
Required documents (bullet points)
For detailed application procedures and FAQs, see: https://www.uni-weimar.de/en/civil-and-environmental-engineering/studies/master-degree-programmes/digital-engineering/application-procedure/
Winter Semester (International)
15 July 2026
Summer Semester (International)
15 January 2027
Winter Semester (EU/EEA)
30 September 2026
Summer Semester (EU/EEA)
31 March 2026
Graduates are prepared for roles at the interface of engineering and computer science, such as digital product and process modelling, simulation and optimisation in construction, mechanical engineering and other industrial sectors. Typical positions include digitalisation engineer, simulation/modeling specialist, data-driven process engineer, and roles in R&D teams focusing on Industry 4.0 solutions.
The programme’s emphasis on applied research and industry collaboration also equips graduates for further academic research (PhD) or technical consultancy roles where advanced modelling, data-handling and cross-disciplinary communication skills are required.
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