This Master's programme prepares students to work at the intersection of established engineering disciplines, computational science and applied mathematics. Alongside theoretical modelling and experimental methods, computer simulation is treated as a core tool for tackling problems that arise in both basic research and product development. The course is designed to train graduates who can translate engineering problems into mathematical formulations and implement numerical software to solve them.
The curriculum goes beyond traditional engineering and applied-mathematics training to build competencies in mathematical modelling, numerical simulation and scientific software development. These skills are applicable across a wide range of technological and research contexts, from analysing complex physical systems to supporting innovation in industry.
Students choose a technical application focus that matches their interests and career goals. Available specialisations include Automatic Control, Computational Materials Science, Computational Mechatronics, Computational Optics, Information Technology, Mechanics and Dynamics, Medical Engineering, and Thermo- and Fluid Dynamics. There is also an option to earn a second Master's degree from the Swiss cantonal Università della Svizzera italiana (USI) in Lugano; the double-degree pathway carries no tuition fees and requires a combined total of 120 ECTS, with at least 30 ECTS completed at USI and at least 30 ECTS completed at FAU.
This Master's programme is organized around four main components: a seminar, three thematic sections (Mathematics, Computer Science, and a Technical Application Field), and a Master's thesis. Although each technical application field (TAF) has a suggested study plan, all modules are elective. Students build their individual study path by selecting courses from the module catalogues of the Computer Science, Engineering, Applied Mathematics, and Physics departments, allowing strong interdisciplinary tailoring toward academic or industry goals.
Key module groupings and how they work:
Learning outcomes and practical experience: Students develop advanced skills in mathematical modelling, numerical analysis, and algorithmic/computational methods, and learn to apply these tools to concrete engineering problems within their chosen technical field. The programme is designed to build research competence and independent problem-solving: the 30‑ECTS Master’s thesis provides a research-orientated capstone where students work under a thesis advisor (often within a research group), practice scientific writing, and present their results orally. The thesis may be written in English; a roughly 30‑minute presentation plus discussion is mandatory.
Requirements (concise)
Applicants must hold an excellent Bachelor’s degree (or an equivalent qualification) in Computer Science, a related scientific or technical discipline, or in Mathematics. Your prior studies must include specific core coursework: Programming and Algorithmics (20 ECTS), Computer Engineering (5 ECTS), Mathematics fundamentals—covering analysis, linear algebra and stochastics—(at least 20 ECTS), and Engineering Sciences related to the technical application subject you select (20 ECTS).
International applicants must demonstrate a solid command of English (see the program’s language requirements for accepted tests and minimum scores). Submission of standardized test results—GRE (Subject Test in Physics and/or Mathematics and/or the General Test) or the Graduate Aptitude Test in Engineering (GATE)—is optional. Prospective students should be prepared to remain in Germany for a minimum of two years. Note: applicants whose Bachelor’s is in Computer Science (or Computer Engineering) or a closely related field but who do not have a distinct engineering specialization are advised to apply to the TAF Medical Engineering track instead.
Admission requirements (summary)
Winter Semester (International)
15 April 2026
Winter Semester (EU/EEA)
15 July 2026
Graduates are prepared for roles that require strong mathematical modelling, numerical simulation and software implementation skills. Typical career paths include positions in research and development, simulation and computational engineering teams, and software development for engineering applications in industry sectors such as automotive, aerospace, energy, medical technology and materials.
The programme also provides a solid foundation for further academic study (PhD) for students interested in research careers, as well as for professional roles that bridge algorithmic methods and practical engineering development.
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