Computational Methods in Engineering (CoME)

Overview

This English-taught Master's programme trains you in the core concepts, methods and software tools for modelling, simulating and analysing complex systems on computers. Advances in computing now make it possible to study phenomena that were previously inaccessible to direct observation—for example, long-term climate dynamics and their impacts on society and ecosystems. The programme emphasises how computational approaches can be used to understand and predict behaviour across many technical and scientific domains.

What you will gain

Graduates emerge as interdisciplinary engineers who work at the intersection of mechanical and process engineering, computer science and mathematics. You will develop deep skills in numerical analysis and the practical simulation of technical problems, enabling you to connect traditional engineering disciplines with modern software development. The course also opens pathways to work with sectors beyond classical engineering through the broad applicability of computational methods.

Structure and learning experience

From the first semester the curriculum integrates modules from computer science, mathematics and various engineering departments, giving early and continuous exposure to a wide range of simulation applications. This tightly connected module structure allows you to explore different fields immediately and then refine your focus through elective choices, while retaining a strong theoretical foundation throughout the programme.

Requirements (concise)

• Bachelor’s degree (German or international) in engineering or a closely related field such as mathematics or computer science
• Programme language: English
• Intended for applicants seeking interdisciplinary training in computational modelling, numerical analysis and simulation techniques

This master’s curriculum is built around a mix of mandatory coursework, hands-on project work, elective specialization and a final research thesis. The taught portion includes an 11-module compulsory core that develops foundational computational and engineering methods, while the elective component lets you choose four technical modules plus one free elective to tailor your skill set. Both the compulsory and elective modules are scheduled across the programme’s first three semesters, giving a clear progression from core knowledge to specialization.

Practical, project-oriented learning is central. The interdisciplinary project area comprises two modules that, together with a dedicated “Simulation Methods in Science and Engineering” project module, are supervised by the programme’s teaching staff and supported by guest lecturers from industry and OVGU. These project modules emphasize real-world topics (including industry and external research institution problems), require team-based solution development, and end with public presentations of your results. The degree concludes with a 30 CP Master’s thesis and an accompanying colloquium, intended to prove your ability to independently and scientifically solve a defined engineering simulation problem within a prescribed timeframe.

Key learning outcomes include the ability to apply and extend simulation methods to research and industry problems, solve complex engineering problems independently and in teams, communicate results publicly, and carry out rigorous, time-bound scientific work culminating in a Master’s thesis.

Requirements (concise)

• Compulsory area: 11 modules × 5 CP each = 55 CP
• Interdisciplinary project area: 2 modules × 5 CP each = 10 CP
• Elective area: 4 technical modules + 1 free elective × 5 CP each = 25 CP
• Master’s thesis: 30 CP, plus presentation in a colloquium
• Compulsory and elective modules are completed during the first three semesters
• Project Work and Simulation Methods modules are project-oriented, supervised by all programme lecturers; topics may come from industry or external research institutions
• Simulation Methods in Science and Engineering includes lectures from industry and OVGU staff and requires group work with public presentation of proposed solutions
• Programme components together amount to 120 CP (arithmetic sum of listed components)

Graduates are prepared to work at the interface of engineering disciplines and software development, taking roles that require strong numerical and simulation skills. Typical career paths include simulation engineer, computational scientist, numerical analyst, or software developer for engineering applications in sectors such as mechanical engineering, process engineering, energy, automotive, aerospace and environmental modelling.

The interdisciplinary training also equips graduates to collaborate across departments and industries, pursue research positions or continue towards a PhD in computational engineering, applied mathematics or computer science.