24 monthsProgramme duration
185,000 SEKTuition Fee/year
AugStarting Month
Programme overview
Main Subject
Physics and Astronomy
Degree
Other
Study Level
Master's
Study Mode
On Campus
Are you interested in combining computational science with the fascinating world of physics? This programme will teach you how to generate and store large volumes of data and use data science to search for patterns, correlations, and trends in issues related to physics.
The programme gives you specialised knowledge in the field of computational science, while also being interdisciplinary in character. You will gain insight into complex processes within physics, and how computational science can contribute to knowledge development in society. You will learn how to use numerical simulations and machine learning to make forecasts and analyses, or to replace experiments.
Computational physics is a branch of computational science in which analytical, numerical and statistical methods are used to analyse and draw conclusions from physics models and large data sets from physics experiments. Examples of focus areas are accelerator physics, cell dynamics, supernovas and environmental and climate changes.
In addition to theory for computational science, there will be an emphasis on the practical tools that are used by professionals in the field, including training your skills in programming. You will also acquire general knowledge and skills of importance for computationally intensive professions, such as problem formulation, information search, data processing, scientific writing, and presentation techniques.
The programme has strong ties to research. You will be taught by internationally well-recognised researchers, and you will be in contact with several research groups.
Programme overview
Main Subject
Physics and Astronomy
Degree
Other
Study Level
Master's
Study Mode
On Campus
Are you interested in combining computational science with the fascinating world of physics? This programme will teach you how to generate and store large volumes of data and use data science to search for patterns, correlations, and trends in issues related to physics.
The programme gives you specialised knowledge in the field of computational science, while also being interdisciplinary in character. You will gain insight into complex processes within physics, and how computational science can contribute to knowledge development in society. You will learn how to use numerical simulations and machine learning to make forecasts and analyses, or to replace experiments.
Computational physics is a branch of computational science in which analytical, numerical and statistical methods are used to analyse and draw conclusions from physics models and large data sets from physics experiments. Examples of focus areas are accelerator physics, cell dynamics, supernovas and environmental and climate changes.
In addition to theory for computational science, there will be an emphasis on the practical tools that are used by professionals in the field, including training your skills in programming. You will also acquire general knowledge and skills of importance for computationally intensive professions, such as problem formulation, information search, data processing, scientific writing, and presentation techniques.
The programme has strong ties to research. You will be taught by internationally well-recognised researchers, and you will be in contact with several research groups.
Admission Requirements
Bachelor´s degree in Physics of at least 180 credits. English course 6/English level 2 (advanced proficiency). or Bachelor’s degree of at least 180 credits in Science or Engineering. The degree should contain at least 30 credits mathematics, of which 6 credits in programming and 7.5 credits in statistics, and an additional 90 credits in mathematics and/or physics. English course 6/English level 2 (advanced proficiency).
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
International
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