Study programme
Four types of courses
Computational Science is an area of science which spans many disciplines and the master’s programme is designed with this in mind. At its core, the programme focuses on the development of models and simulations to understand natural systems. Within the programme there are 4 course types: compulsory core courses, restricted-choice elective courses, restricted-choice professional skills elective courses and free-choice elective courses. A standard study plan consists of 13 courses (78 EC - 6 EC per course) and a graduation project (42 EC, 7-9 months).
- The core compulsory courses reflect the central body of knowledge in Computational Science.
- The restricted-choice courses offer breadth and depth, allowing you to either deepen your knowledge on core topics or broaden your scope.
- The free-choice elective courses offer the option to take courses in application domains. These are especially intended for students who would like to do a research graduation project in one of the application domains as described below.
- The restricted-choice professional skills elective courses that strengthen the professional knowledge and skills required by the professional field (e.g. academic writing, performing academic research, academic analysis).
Please note that the number of courses in the curriculum may deviate depending on the chosen elective courses. For detailed information regarding the curriculum and courses, please see the UvA Course Catalogue.
A study plan may differ per student and students are allowed to design their own study plan with the condition that the CLS Examinations Board has to approve the study plan in question.
Course information
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The first year
The first year is dedicated to core Computational Science courses covering computing & algorithms, modelling & simulation, massive-data processing and multidisciplinary collaboration.
During the first year, the restricted-choice courses and free-choice elective courses are in addition to your core compulsory courses and can be chosen freely from an extensive list.
The restricted-choice courses also include central concepts in Computational Science, but here we offer some choice. These courses allow you to broaden your knowledge in either computing or modelling & simulation.
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The second year
The restricted-choice courses also include central concepts in Computational Science, but here we offer some choice. These courses allow you to broaden your knowledge in either computing or modelling & simulation.
The free-choice elective courses help you prepare for the Master Thesis Computational Science. The Master Thesis Computational Science will be conducted in a scientific group at one of the universities in Amsterdam, but could also take place at institutes at the Science Park, such as CWI, NIKHEF, AMOLF, AMC and the NKI, outside Amsterdam or abroad. Often students who choose Finance & Economics will do their Master's thesis at a financial institute such as 'de Nederlandse Bank'. The Master Thesis Computational Science has to be a scientific project with the potential to complement the existing body of knowledge in Computational Science.
Good to know: the annual UvA Thesis Fair connects experts from industry with students of informatics, resulting in innovative graduation thesis projects. Find out more about the UvA Thesis Fair.
Computational Science thesis projects often result in a publication in a scientific paper. Here you can download a list of publications of our Master's students.
Master Thesis Computational Science
Here are some abstracts of recent examples of Master's theses of our graduates:
In the MSc Computational Science, you will learn:
- to build computational models from real-life observations;
- to develop skills in turning these models into computational structures and perform large-scale simulations;
- the theory that gives you a firm basis for the analysis of complex simulations;
- to analyse the results of your simulations in a virtual laboratory using advanced numerical algorithms;
- to control the power of the largest supercomputers.
To achieve these goals, you will have access to some of the most advanced computing, networking, storage and visualisation facilities in the world.
Graduation in different application domains
Not only do you graduate with knowledge of the core concepts of Computational Science like complex network simulation, but you can also specialise in one of the application domains, such as Computational Biology or Computational Finance. You can use the elective courses to take specific courses in application domains and perform your research in helping solving domain-specific problems in collaboration with domain experts.
Pre-Master's programme
The Admissions Board may decide that you do not meet the entry requirements for admission to the Master’s programme. In some cases, they give the student in question the advice to do a Pre-Master’s programme first. Those students can submit a request for admission to the Minor Computational Science (30 EC) at the UvA. This minor programme is the Pre-Master’s programme and will train you in mathematics and programming in preparation for the Master's programme. The minor programme runs from September to January. Students who successfully complete the minor programme will be admitted to the Master’s programme in the subsequent academic year.
Accreditation and academic title
Degree requirements
A Master of Science in Computational Science is awarded upon successful completion of all the core courses in the curriculum and a written Master's thesis based on an independent research project. This translates into a total of 120 EC credits.
Accreditation
The Master's programme in Computational Science has been legally accredited by the Accreditation Organisation of the Netherlands and Flanders (NVAO). This means that upon successful completion of the programme, you will receive a legally accredited Master's degree in Computational Science and the title of Master of Science (MSc).
Bring your own device
All students enrolled in Computational Science are requested to bring their own laptop due to the nature of the programme. More information on specific system requirements can be found here.