Computer simulations of complex problems and management of large data sets (big data) play a key role in today’s scientific studies and engineering design. The Master Programme in Computational Science provides you with the opportunity to broaden and deepen your knowledge of natural science or technology, with a specialisation in computers, large data sets, computer simulations and mathematical modeling. You will learn to apply computational methods, programs and software, as well as mathematical and statistical models, within your sphere of interest.
Large or small, at the macro or micro level – various phenomena are today studied on a computer screen. To be able to use, develop and apply computer simulations within a certain subject area requires not only a solid background in the actual subject field such as chemistry or physics, but also computational methods, advanced computers, software, algorithms, programming, as well as statistical and mathematical models. The Master Programme in Computational Science provides you with this knowledge.
Computational science is a multidisciplinary field where issues in areas such as chemistry, biology, physics, finance and geosciences are studied, using advanced computers and software to perform numerical simulations based on mathematical and statistical methods.
Why this programme?
The multidisciplinary character of computational science is reflected in the content of the Master Programme in Computational Science and contains a wide range of elective courses. You can choose between five recommended tracks of courses or you can tailor your own track depending on your educational background and areas of interest with regard to applications in science. The five recommended study tracks are:
Numerical and mathematical modeling
At least 30 credits of the courses you choose must be in the field of computational science and at least 30 credits must be in one of the fields chemistry, biology, physics, geoscience, computer science or mathematics.
The programme leads to a Master of Science (120 credits) with Computational Science as the main field of study.
You can choose to follow one of the five recommended study tracks or you can set up your own track with support from the student counsellor. The courses will then depend on your individual choices.
The five different study tracks consists of a package of preselected courses that gives you a specialisation into the specific field and these are:
Numerical and mathematical modeling: Here your get knowledge about how different mathematical models works and how you can compute the solutions with numerical methods.
Computational physics: Here you get knowledge about how to apply computational methods in problems in physics and at the same time you will focus on some area of physics, e.g., fluid dynamics.
Computational chemistry: Here your will get knowledge about how to apply computational methods for mathematical models in chemistry and at the same time you will focus on some area of chemistry, e.g., molecular dynamics.
Computational finance: Here you get knowledge about how to apply computational methods in financial mathematics and at the same time you deepen your knowledge in financial modeling, e.g., in the stock and option market.
Data engineering: Here you get knowledge about how to construct systems for handling and extracting information from very large data sets with the help of, e.g., cloud computing, distributed systems for large scale data analysis and methods in database techniques.
Each track has a recommended set of courses but the exact content in each track still depends on your specific background with previous courses and experience and is put together in dialogue with the student counsellor.
The instruction consists of lectures, group work, project work and assignments. The pedagogy is student centered and puts a large emphasis on activating instruction building up practical skills that are directly useful in your coming profession. The instruction is in English and conducted in close connection with current research. In addition to the thesis work carried out throughout the final semester, a broader project course is included in the programme. In this project course you apply skills in computational science to a problem originating in academia or industry, while the course provides training in project work and management. The programme takes place in Uppsala.
Today, numerical simulations on computers based on mathematical and statistical models, plays a key roll in natural sciences and technology. Experiments and simulations produce enormous data sets and methods for drawing conclusions from these becomes more and more common. It has become a new way to search for knowledge and to create new products. In industry, as well as in research, computer simulation has become an important tool. In some cases as a complement to experiments and in some cases there is no possibility to do experiments and you are only referred to computer simulations. For industry computer simulations are attractive as you can do these quicker and for a smaller cost, it is more cost efficient.
Computers are used to study problems within sectors where experiments are expensive or impossible to perform, or where systems are so complicated that simplified assistance models are insufficient. Important examples can be found within the environmental industry and the energy sector. The use of tools based on computer calculations and simulations is currently increasing substantially within companies of different sizes and within many different sectors. Computer simulations can be performed within many areas such as weather forecasts, design of pharmaceuticals, car crash simulations, development of new aircraft, or studies of climate change. Computer simulations play a central role for increased understanding and product development within these areas, as well as in determining performance and other qualities for processes and products, or to optimise design and quality.
The interdisciplinary content of the programme provides you with unique skills currently in demand in the labour market. There is an increasing need of qualified manpower that can combine scientific knowledge with mathematical modeling, programming of advanced computer systems, large scale data analysis and proficiencies in using modern computational scientific tools. This combination is important, and a rapid increase in demand for qualified people with such combination is expected – both in Sweden and internationally.
The professional career may be in scientific or technical research and development, as scientific and/or technical advisor, consultant or project leader. The programme also prepares you for PhD studies in e.g. computational science, physics, bioscience, and mathematics.
Requirements: Academic requirements A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university. The main field of study must be within science, engineering, mathematics or computer science. Also required is:
30 credits in mathematics, including algebra, linear algebra, calculus and vector calculus;
5 credits in programming; and
5 credits in numerical methods (numerical analysis or scientific computing).
Language requirements All applicants need to verify English language proficiency. This is normally attested by an internationally recognised test such as TOEFL or IELTS with the following minimum scores:
IELTS: an overall mark of 6.5 and no section below 5.5
TOEFL: Paper-based: Score of 4.5 (scale 1–6) in written test and a total score of 575. Internet-based: Score of 20 (scale 0–30) in written test and a total score of 90
a total appraisal of quantity and quality of previous university studies; and
a statement of purpose (1 page).
Tuition fee-paying students and non-paying students are admitted on the same grounds but in different selection groups.
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees. Fees cover application and tuition only and do not cover accommodation, academic literature or the general cost of living. Read more about fees.