Description The MSc in Computational Sciences is an interdisciplinary Master’s programme run by the Faculty of Mathematics and Natural Sciences. It trains students to use computational approaches—modelling, simulation and data science—alongside advanced computer science and applied mathematics to address open questions in the natural sciences. The curriculum is designed to give both broad computational skills and deep domain knowledge in a chosen specialty.
Students pick one of five areas of specialisation and tailor their coursework and research accordingly. The programme balances taught modules on simulation and modelling techniques with subject-specific lectures so you develop both methodological expertise and applied understanding in your field.
The degree culminates in a research-focused Master’s thesis carried out within the selected specialisation, allowing you to apply the computational methods learned to a substantive research question. The programme is taught in English, making it suitable for international students seeking an interdisciplinary, research-oriented Master’s in computational methods for the natural sciences.
Requirements (program structure and key facts)
The curriculum builds a strong computational foundation and then guides you into a focused research specialisation. The two core modules, Simulation and Modelling I and II, cover techniques from numerical modelling to machine learning and use practical examples drawn from all specialisation areas. Each of these modules is worth 9 CP and is scheduled for the first and second semesters respectively, so you apply computational methods early and continue developing them across your studies.
You will deepen your theoretical and technical skills through an Elective Mathematics and Computer Science area (18 CP) where, together with your mentor, you pick advanced topics from departments across the Faculty of Mathematics and Natural Sciences. The heart of the program is the Area of Specialisation: 30 CP of taught courses (spread across semesters 1–3), plus a research sequence—literature seminar (6 CP), a project (12 CP, intended in semester 3) and the Master’s thesis (30 CP, in semester 4). For most specialisations you must take two compulsory core modules (combined 12 or 15 CP depending on the specialisation), with the remaining credits chosen from a catalogue of basic and advanced modules. Earth System Sciences is an exception: there are no compulsory modules and you select a total of 30 CP from its basic and advanced offerings.
The program emphasizes independent research skills. The literature seminar, project work and thesis are compulsory and are carried out within a research group in your specialisation, preparing you for research-oriented careers or doctoral studies. A flexible Supplementary Module (6 CP) can be taken in any of the first three semesters from a wide selection of courses—including offerings such as the Excellence Startup Center Gateway, digital humanities, mathematics and computer science, or other specialisation modules—allowing you to broaden your interdisciplinary profile.
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This interdisciplinary master's program expects applicants to come from a quantitative Bachelor of Science background and to have solid foundations in mathematics and programming. Because the curriculum integrates methods from several scientific domains, you should already have completed coursework in math and/or computer science and demonstrated ability in a high-level programming language. You also need subject-specific credits in one of the listed application areas so you can follow the domain-specific components of the program.
"CP" refers to credit points (Leistungspunkte), commonly aligned with the ECTS credit system in European universities. Proof of programming skills can be a course certificate, project report, or a thesis that clearly shows your experience with a higher-level programming language.
Admission requirements (summary)
Winter Semester (International)
15 July 2026
Winter Semester (EU/EEA)
15 July 2026
Graduates are prepared for research-oriented careers in academia and research institutes as well as for specialist roles in industry that require advanced computational modelling, simulation and data-analysis skills. Typical employers include university and government research groups, climate and earth-system modelling centres, space and astrophysics organisations, biotech and pharmaceutical companies, and high-performance computing and software firms.
The programme's strong methodological training and integrated thesis project also provide a solid foundation for doctoral studies (PhD) in computational sciences, applied mathematics, computer science or discipline-specific research fields related to the chosen specialisation.
Trier University of Applied Sciences — Birkenfeld
Technische Universität Braunschweig — Braunschweig
Furtwangen University — Villingen-Schwenningen
University of Siegen — Siegen