Engineering mathematics and computational science, MSc

120 credits (2 years)

Gain a solid foundation in mathematics and the skills to formulate and solve many of the problems that are posed by the industry, business and research.​

Engineering mathematics and computational science​ master's programme at Chalmers

Nowadays, one can without hesitation, state that there is mathematics in virtually everything. There is mathematics behind mobile phones, cars and oil tankers. Internet is built on mathematics and Google is based on probability theory. Cryptology and secure data transfer are based on classical number theory.New mathematical methods are necessary for understanding modern physics and chemistry, e.g. advanced mathematical and statistical models are required in climate science.
Bioinformatics has quickly grown to become one of the big areas of applied mathematics. Continuing the development of mathematical methods is necessary in order to deal with the huge amounts of information generated by e.g. gene mapping. 

The master's programme provides a solid base in mathematics and/or mathematical statistics or computational science. It is also possible to choose a direction towards bioinformatics. We also offer a number of courses in financial mathematics.
On completion of the master's programme, you will be able to not only master a given area of engineering but also take part in the development of mathematical models and algorithms.
Engineering mathematics and computational science master's programme turns to you who wants to sharpen your engineering studies with state-of-the-art mathematical competence as well as to you who with a keen curiosity-driven mathematical interest. Of course, it also turns to you who have realised that deep mathematical knowledge is on-demand in an ever-increasing number of areas. 

Topics covered 

The subjects of mathematical statistics, computational science and engineering mathematical modeling are fundamental areas in the Engineering Mathematics and Computational Science master’s programme. The courses included in the programme plan handle topics such as engineering mathematics, applied mathematics, mathematical biology, machine learning, big data science, pure math and mathematical physics.

Master's programme structure 

The master's programme runs for a duration of two years, leading to a Master of Science (MSc) degree​. During each year, students can earn 60 credits (ECTS) and complete the programme by accumulating a total of 120 credits. Credits are earned by completing courses where each course is usually 7.5 credits. The programme consists of Compulsory courses, Compulsory elective courses and Elective courses.

Compulsory courses year 1

During the first year of the programme there are four compulsory courses that form a common foundation in Engineering Mathematics and Computational Science. Each course is 7.5 credits.
  • High performance computing
  • Nonlinear optimization
  • Statistical inference
  • Partial differential equations (can be substituted for a compulsory elective course if student has taken a similar course previously)​

Compulsory courses year 2

During the second year there is one compulsory course  (Project course in mathematical and statistical modelling). 
In addition, in order to graduate, a master's thesis must be completed. The thesis may be worth 30 credits or 60 credits depending on your choice.

Compulsory elective courses *profile, or elective course (choose 3 or more)

Through compulsory elective courses, you can then specialize in one of the following profiles. Profiles provided are mere suggestions. It is not required to adhere these profiles. Students are encouraged to create their own customized, individual profiles based on their particular interests and motivation.​

Profile: Mathematical biology

  • Intro to bioinformatics
  • Computational biology
  • Systems biology
  • Linear statistical models

Profile: ​Financial mathematics

  • Options
  • Financial derivatives and PDE
  • Financial time series
  • Stochastic calculus​

Profile: Machine learning

  • Algorithms
  • Large scale optimization
  • Artificial neural networks
  • Stochastic optimization algorithms

Profile: Big data science

  • ​Linear statistical models​
  • Large scale optimization
  • Statistical learning for big data
  • Artificial neural networks​

Profile: Engineering

  • PDEs
  • Mechanics of solids
  • Mechanics of fluids
  • Computational fluid dynamics​

Profile: Pure math and mathematical physics

  • Algebra 
  • Integration theory
  • Functional analysis
  • Foundations of probability theory

Programme plan, syllabus, course description and learning outcomes​

Other master's programmes that might interest you
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Career

Up to date, roughly half of our ex-students have stayed in academia, i.e. as PhD students, in Sweden as well as abroad. Others have become employed in industry, for example in the automotive industry and the pharmaceutical industry or as consultants for industry.

Research within Engineering mathematics and computational science​​

Research in mathematical sciences, in Sweden and elsewhere, is very intense. Mathematical research in on demand from an increasing number of sectors and at the same time mathematics continues to flourish as a research are in its own right.
These directions of research are not in opposition to each other. On the contrary, they enrich and inspire each other. It is a fact that many of the mathematical results that are of very concrete use today, were developed by pure mathematical curiosity, sometimes decades or even centuries ago.
Swedish mathematical research is by tradition strong. In particular this is true also for the Department of Mathematical Sciences at Chalmers and Gothenburg University. The Department is joint for the two universities, which helps to give it the size needed to create a stimulating environment, socially and scientifically.
A number of Master's students have continued their studies at the department towards a PhD.

​​Student Blogs​

Page manager Published: Wed 14 Apr 2021.