Master's programme in Applied and Computational Mathematics

Students from the Master’s programme in Applied and Computational Mathematics will become skilled applied mathematicians, well-prepared for advanced industrial positions or continued graduate studies. The programme contains five tracks: Computational Mathematics, Financial Mathematics, Mathematical Statistics, Optimization and Systems Theory, and Statistical Learning and Data Analytics.

Application open

Application is open until April 18 2017.

16 January 2017: Application deadline
1 February 2017: Deadline for supporting academic documents (all applicants) and documentation of fee exempt status (if required) or receipt of application fee (if required)
24 March 2017: First notification of selection results
12 April 2017: Last date to reply to your offer

Non-EU/EEA/Swiss citizens: The full programme tuition fee is SEK 310 000
Non-EU/EEA/Swiss citizens are generally required to pay an application fee of SEK 900.

EU/EEA/Swiss citizens: There are no tuition fees for EU/EEA/Swiss citizens
EU/EEA/Swiss citizens are not required to pay an application fee.

Degree awarded: Master of Science
Duration: Two years (120 ECTS credits)
Location: KTH Campus, Stockholm
Programme start: Late August
Language of instruction: English

Programme team:

Applied and Computational Mathematics at KTH

The programme consists of foundation courses that are mandatory for all students, and once the individual specialisation track is chosen, there are relevant required courses within that area as well.

Within the Mathematical Statistics  track students are provided with the ability to analyse and model situations where randomness and uncertainty are common and applicable in several areas.

Financial mathematics is applied mathematics used to analyze and solve problems related to financial markets. Portfolio theory and quantitative risk management present theory and methods that form the theoretical basis of market participants’ decision making.

Statistics is the science of learning from data. Classical statistics is trying to understand data by determining a plausible model for data, and testing whether the data fits the model. Modern learning is concerned with computational statistics and automated methods for extracting information from data.

The Computational Mathematics track contains courses providing knowledge of design, analysis and application of numerical methods for mathematical modeling, usable in computer simulations catering to both research and prototyping.

Finally, the Optimisation and Systems Theory track focuses on the ability to provide optimal solutions within certain restraints, applicable in areas such as economics, operation analysis, biology and robotics, where these dynamic systems are modeled and controlled with assets gained from the systems theory area.



Advanced mathematics and computer simulations are present within several important fields, their use having increased dramatically by the rapid development in computer software and hardware. Financial mathematics, medicine and biology are prevalent areas, but students will be able to bring the usage of mathematics and simulations into a multitude of applications.


For questions regarding programme content and specific admission requirements, feel free to contact the programme director.

Programme team:

Changes in the programme may occur.

Top page top