Computational Engineering - Master

In this programme, students learn to apply mathematical and numerical models to analyse complex and uncertain systems. The insights gained are used to make better decisions that improve performance, quality, and workflows.

Objectives, content, and organisation of the study programme

The programme is designed to offer students great flexibility in shaping their own educational paths. During the first semesters, students acquire competence in fundamental modelling tools and methods, including physical and machine learning modelling, programming, and decision analysis. They can then specialise in different fields by selecting from a wide range of elective courses across engineering disciplines.

Project work is an integral part of the programme. Students engage with realistic problems and learn to present and communicate their results professionally to audiences with diverse backgrounds. The programme is international — Norwegian and international students study together, and all courses are taught in English.

The master’s programme introduces and illustrates a methodology built on mathematics, statistics, and basic programming from a bachelor’s degree in engineering or science.

To better align with students’ career interests and work-life needs, the programme offers two options for the master’s thesis: a one-semester (30 ECTS) or a two-semester (60 ECTS) project. In the latter option, students take fewer courses and dedicate more time to an in-depth qualifying project relevant to their specialisation, further tailoring their education to their professional goals.

The programme covers advanced topics in:

• Modelling and algorithms (physics-driven and applied machine learning)
• Decision analysis
• Optimisation and uncertainty quantification

The master's programme in Computational Engineering runs over four semesters (120 ECTS). Of these, 30 ECTS come from courses that establish a common foundation in modelling, programming, and decision-making. The remaining 90 ECTS consist of either:

60 ECTS of specialisation courses and a 30 ECTS master’s thesis, or

30 ECTS of specialisation courses and a 60 ECTS master’s thesis.

The master’s thesis is a major independent project completed in the final semester(s), often in close collaboration with an external company.

Courses typically include weekly lectures and mandatory hand-in projects as part of continuous assessment. Many courses are also available online (although physical attendance is strongly recommended, and lectures are streamed when possible). Students receive training in report writing and effective communication of results to a broader audience. Programming and data analysis form an integral part of most courses.

Details on teaching and learning methods, required literature, evaluation methods, and assessment criteria are provided in each course description.

The programme also addresses dynamic decision-making under uncertainty and offers courses integrating carbon management strategies with traditional financial metrics. Students learn to evaluate projects that achieve both sustainability and profitability goals. Without rigorous forecasting and computational engineering, energy companies risk making poor decisions that hinder progress toward clean energy.

The University of Stavanger strives to deliver all study programs as planned; however, it reserves the right to make adjustments should there be insufficient resources and/or student enrollment to ensure implementation. Over time, it is expected that both the academic content and the range of courses will evolve in response to developments within the discipline, advancements in technology, and broader societal changes.