Computer Simulation in Science (MSc)

Program overview

This interdisciplinary MSc trains you in the design, implementation and use of computer-based simulation methods to tackle cutting‑edge research questions in the natural sciences and engineering. The curriculum emphasizes practical numerical techniques and software development so you can translate theoretical models into working simulation tools for real research problems.

All courses are taught in English. You select one area of advanced study from a range of specialties: atmospheric physics, computational electromagnetics, computational finance, computational fluid mechanics, detector physics, imaging in medicine, molecular and materials modelling, or theoretical particle physics. The programme is research-oriented and places substantial emphasis on hands‑on computing through lab work and project-based learning.

To support intensive computational training, the university has installed a parallel computer dedicated to this Master’s programme, and extensive computer lab courses are integrated into the curriculum. The programme also maintains contacts with Trinity College Dublin and FZ Jülich (established in January 2009), providing additional academic and research linkages.

Requirements

• Preliminary knowledge at the Bachelor’s level in the chosen subject area
• Knowledge of at least one programming language

Curriculum overview

After you choose your area of advanced study, the programme is built mainly from compulsory courses. The course load is designed to develop independent, responsible working habits: expect substantial weekly homework in every class and regular student presentations that also serve as preparation for the Master's thesis. The programme emphasises practical and transferable skills—problem solving, scientific communication, and self-directed project work.

The MSc opens with an intensive block course in mathematical foundations. This block begins one week before the official start of the teaching term, runs for two weeks and is followed by an examination. Detailed course descriptions are collected in the module reference book (module handbook), which should be consulted for syllabus-level information and assessment formats.

Learning outcomes include a solid mathematical grounding for computational science, the ability to apply simulation methods across interdisciplinary problems, strengthened independent research and time-management skills, and experience presenting and defending project work in preparation for the Master’s thesis. Assessment takes place through weekly assignments, presentations and formal exams, including the block-course exam.

For practical matters—start dates, exact timetables, handbooks and downloadable programme PDFs—check the programme website. For academic questions contact csis@uni-wuppertal.de; for general enquiries such as admission or language-course recognition contact intsek@uni-wuppertal.de. Additional school information is available via the School of Mathematics and Natural Sciences’ LinkedIn and Instagram pages and in downloadable programme documents linked on the website.

Key requirements and contacts

• Programme mainly consists of mandatory courses once you select your advanced-study field
• Expect substantial weekly homework across all courses
• Regular student presentations are required and are part of Master’s thesis preparation
• Mandatory two-week block course on mathematical foundations starts one week before the teaching period and concludes with an examination
• Consult the module reference book (module handbook) for detailed course descriptions and assessment information
• Check exact dates and timetables on the programme website: https://www.csis.uni-wuppertal.de/en/
• Academic enquiries: csis@uni-wuppertal.de
• General enquiries (admission, language-course recognition, etc.): intsek@uni-wuppertal.de
• Further information and downloadable PDFs available via the programme site; school updates on LinkedIn and Instagram

Graduates are prepared for roles that require advanced simulation, modelling and high-performance computing skills. Typical career paths include research and development positions in academia and research centres, computational scientist or simulation engineer roles in industry sectors such as engineering, finance, medical imaging and materials, and software development positions focused on scientific computing and HPC.

The programme also provides a solid foundation for pursuing doctoral studies (PhD) in computational science and related disciplines, as well as for roles that require specialised expertise in numerical methods, data-driven simulation and parallel computing.