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Lund University
Master Programme in Computational Science, Scientific Computing
<p>This Master’s programme gives you specialised knowledge about methods used in computational science and how to apply them. You will be able to deep-dive into numerical simulations and machine learning to make forecasts and analyses, or to replace experiments. You will learn how to generate and store large amounts…
- Higher education
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- 31 August 2026
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Overview
<p>This Master’s programme gives you specialised knowledge about methods used in computational science and how to apply them. You will be able to deep-dive into numerical simulations and machine learning to make forecasts and analyses, or to replace experiments. You will learn how to generate and store large amounts of data and use data science to search for patterns, connections, and trends in issues related to the natural sciences.</p><p>Advanced computations are increasingly important in research and business. In this Master’s programme you will learn how to study complex processes within the natural sciences, and how computational science can contribute to knowledge evolution in society. Scientific computing focuses on the study and development of computational methods that are used within computational science. A few of many examples are studies in, and research on, environment and climate change to the specific design of new aviation fuel or understanding supernovas.</p> <p>The programme prepares you for a future career in academia or business. In addition to theoretical knowledge in computational science, there will be an emphasis on obtaining knowledge about the practical tools that are used by professionals in the field, including training your skills in programming. You will get general knowledge and skills of importance for computationally intensive professions, such as problem formulation, searching for information, data processing, scientific writing, and presentation techniques.</p> <p>The Master’s programme gives you specialised knowledge in the field of scientific computing, while also being interdisciplinary in character. Participating students have a background in maths/physics and an interest in mathematics and programming, but you will take courses alongside students from other specialisations. In this context, there will be a chance to conduct joint projects and degree projects. The programme has strong ties with research. You will be taught by internationally well-recognised researchers, and you will be in contact with several research groups. The programme is taught in English.</p> <p> </p> <p><strong>Programme structure</strong></p> <p>The programme puts emphasis on mathematics, numerical analysis and mathematical statistics. The course design combines numerical methods for differential equations with mathematical statistics and natural sciences to provide you with knowledge and skills for differential equation-based and data-based modelling. </p> <p>In the first year, you will study four compulsory courses: modelling in computational science, Monte Carlo methods for statistical inference, stationary stochastic processes and numerical methods for differential equations. You then go on to choose courses such as artificial neural networks, simulation tools, statistical modelling of extreme values and numerical algorithms with Python/SciPy. You can also choose from a selection of courses with focus on different processes in the natural sciences. The degree project is worth 30 credits.</p> <p> </p> <p><strong>Career opportunities</strong></p> <p>Graduates of the programme can embark on several different career paths. The Master’s programme gives you a good foundation for third-cycle studies in the natural sciences, or a career within industry or business. You can thus also choose a career path outside academia and then find attractive jobs in areas where there is a need to solve natural science problems with the help of statistics, data processing or simulations, in industry or in public administration and other organisations.</p><p>https://www.maths.lu.se/english/education/masters-programme-in-computational-science/</p>
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Entry requirements
Specialisation in Scientific Computing Bachelor´s degree in Physics of at least 180 credits. English course 6 (advanced proficiency) or Bachelor’s degree of at least 180 credits in Science or Engineering. The degree must contain at least 30 credits mathematics, of which 6 credits in programming and 7.5 credits in statistics, and an additional 60 credits in mathematics and/or physics. The degree must contain at least 15 credits in a natural science (not mathematics) or in computer science. English course 6 (advanced proficiency) Other information Some of the optional courses within the program may have higher requirements in mathematics or in other natural science subjects.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
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- Skolverket Susa-navet
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- 2026-08-31
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- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
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- Education offering e.uoh.lu.naber.18172.20262
- Last checked
- 2026-09-23T10:38:33.477975+00:00
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- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
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Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
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- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.lu.naber.18172.20262
- Offering identity in the source
- e.uoh.lu.naber.18172.20262
- Education-form source code
- HS
- Education code in the source
- NABER
- Change time according to the source
- 2026-02-10T09:36:45
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.