This English-taught Master’s programme offers an interdisciplinary engineering education that links chemistry, physics, mathematics and multiple engineering and information disciplines. It responds to today’s complex technological and societal challenges by training students beyond single-discipline specialisations: you will learn to integrate fundamentals from chemistry, electrical and mechanical engineering, computer science, information technology and physics to understand and engineer advanced materials for real-world applications.
A distinctive feature of the programme is its emphasis on probabilistic and predictive approaches. Instead of relying solely on deterministic models, the curriculum introduces stochastic modelling and uncertainty quantification early on so you can predict material behaviour, assess risks, and characterise the reliability of engineered systems. The course work and projects develop the ability to mathematically and physically model coupled technical–physical systems while explicitly accounting for the properties of the materials involved.
This Master’s prepares you for both industry and research careers: you will gain practical skills to design and carry out interdisciplinary, scientific projects in materials science applied across many technology sectors, and you will acquire the methodological and cognitive tools needed to pursue independent research or continue into a PhD programme. The combination of broad disciplinary grounding and a modern, probabilistic outlook is particularly useful if you plan to work on complex, data-driven materials problems or in R&D teams that cross traditional engineering boundaries.
Learning outcomes (what you will be able to do upon graduation)
The programme runs over four semesters. In the first year (semesters one and two) you build a rigorous, disciplinary foundation through mandatory modules that cover core topics such as materials science, multiscale modelling, numerical methods, non-linear fluid and solid mechanics, and uncertainty quantification. By the end of this phase you will be able to apply multiscale thinking to materials problems, use numerical techniques for modelling complex mechanical behaviour, and assess and quantify uncertainty in computational and experimental workflows.
From semester two onwards you begin to specialise across one of four thematic tracks: Multiscale Material Principles; Materials in Engineering Applications; Uncertainty Quantification & Mathematical Modelling; or Material Characterisation, Testing & Surveillance. Specialisation is implemented in two stages—Area I (specialisation-specific modules drawn from a defined set in the module catalogue) and Area II (broader individual electives chosen to tailor your profile). Practical and transferable research skills are integrated into the programme: scientific-skills modules are recommended in semesters two and three, and the curriculum includes required and elective internship modules. A distinctive feature is the Advanced Research Internship (recommended in semester three), where you join an established research group and produce a supervised scientific paper, offering a first independent research contribution. The programme culminates in the Master’s thesis in semester four.
Curriculum requirements (concise)
Sample curricula for each specialisation are available in the module catalogue to help plan course sequences and elective choices.
This master's programme requires a relevant, university-level Bachelor’s degree and successful completion of the programme’s aptitude assessment. Admissions focus on whether your prior studies provide the technical foundations needed for advanced work in materials science and engineering. International applicants should be aware that additional test scores or documentation may be requested if your Bachelor’s curriculum differs substantially from the programme’s expectations.
Some applicants must also provide standardized test results as evidence of subject-related competence, and all applicants must demonstrate adequate English language ability. Selection is carried out through a two-stage aptitude assessment after you submit an official application: first a points-based review of your Bachelor’s grades and written documents, then—for some applicants—an interview. If you are not successful the first time, you may repeat the aptitude assessment once. Detailed information on required test scores, accepted language certificates, and other formalities is published on the programme’s website.
Admission requirements (summary)
Winter Semester (International)
31 May 2026
Winter Semester (EU/EEA)
31 May 2026
Graduates are prepared for research and development roles in industry and research institutions where advanced materials, modelling and testing are central — for example in aerospace, automotive, energy, electronics, medical devices and materials engineering firms. The programme's emphasis on predictive science, uncertainty quantification and multiscale modelling equips you to work on material design, testing, reliability assessment and simulation-driven development.
The degree also provides a strong foundation for academic careers: methodological and research skills developed through the Advanced Research Internship and the Master’s thesis make the programme a direct pathway to PhD programmes and further research positions in universities and public or private research centres.
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