Tillfället ingår inte i den aktuella katalogen. Uppgifterna är bevarade från en tidigare publicering. Kontrollera aktuellt utbud hos anordnaren.
Lund University
Master Programme in Computational Science, Life Sciences
<p>Within the life sciences, there is a significant demand for expertise in computational science. On this programme you will learn how to generate and store large amounts of data and use data science to search for patterns, correlations, and trends in issues related to medicine and biology.</p><p><strong>About the…
- Högskoleutbildning
- Uppgift saknas
- 31 augusti 2026
- Uppgift saknas
- Uppgift saknas
- 100 %
Översikt
<p>Within the life sciences, there is a significant demand for expertise in computational science. On this programme you will learn how to generate and store large amounts of data and use data science to search for patterns, correlations, and trends in issues related to medicine and biology.</p><p><strong>About the program</strong></p> <p>There is currently an explosive growth in computational science methods within medicine and biology. This master’s programme will teach you how to study complex processes within life sciences, and how computational science can contribute to knowledge development in society. You will gain knowledge in the use of numerical simulations and machine learning to make forecasts and analyses, or to replace experiments.</p> <p>The programme gives you specialised knowledge within computational science, while also being interdisciplinary in character. The education contains a mixture of courses in</p> <p>biophysics, systems biology, mathematics and computational science. You will, for example, learn about dynamic modelling of various processes in cells and organs, and you will gain knowledge in artificial intelligence, with a focus on deep learning.</p> <p>In addition to theoretical knowledge in 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.</p> <p>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.</p> <p> </p> <p><strong>During your studies</strong></p> <p>The proportion of teacher-directed learning is high, and you will gain experience in collaborating in groups. The programme is offered in English.</p> <p>The programme includes six compulsory courses. They cover modelling in computational science, numerical methods for differential equations, introduction to artificial neural networks and deep learning, cell biology, theoretical biophysics, and systems biology.</p> <p>In addition, you will be offered elective courses in areas such as reproducible data analysis and statistical learning, uncertainty quantification and data-driven modelling,</p> <p>spatial statistics with image analysis, experimental biophysics, and linear and logistic regression. You may also choose optional courses within science or medicine. The last term is reserved for your thesis.</p> <p>Participating students have a background in mathematics, programming and physics and an interest in applications in medicine or biology, but you will take courses also with students from other specialisations. In that context, there is an opportunity to carry out projects jointly and to collaborate on your individual theses.</p> <p> </p> <p><strong>After your studies</strong></p> <p>Advanced computations are increasingly important in research and business. There is a significant demand within the life sciences for computational expertise in data-driven analysis and modelling of dynamic systems related to medical and biological questions. The field of health is considered to hold particularly strong potential in the application of artificial intelligence.</p> <p>Graduates of the programme can embark on several different career paths. The master’s programme gives you a solid foundation for third-cycle education in science but also prepares you for a career within industry or business, particularly within the pharmaceutical industry. You can thus choose a career path also outside academia and find attractive jobs in areas where there is a need to solve science problems with the help of statistics, data processing or simulations.</p><p>https://www.maths.lu.se/english/education/masters-programme-in-computational-science/</p>
Antagningspoäng
Behörighet
Bachelor´s degree in Physics of at least 180 credits. Proficiency in English equivalent to English 6 from Swedish upper-secondary school. or Bachelor’s degree of at least 180 credits in Science or Engineering. The degree should contain: 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 15 credits in science other than mathematics Proficiency in English equivalent to English 6 from Swedish upper-secondary school.
Texten återges från Susa-underlaget. Antagningsdata gör ingen egen mappning mellan GY11 och GY25 och bedömer inte personlig behörighet.
Källa, mått och datakvalitet
- Källa
- Skolverket Susa-navet
- Period
- 2026-08-31
- Mått
- Behörighetstext återgiven från publicerat Susa-underlag; ingen personlig behörighetsbedömning.
- Population
- Utbildningstillfälle e.uoh.lu.naber.18173.20262
- Senaste kontroll
- 2026-09-23T10:38:33.477975+00:00
- Begränsning
- GY11 och GY25 mappas inte av Antagningsdata. Grundläggande och särskilda villkor separeras inte utan strukturerat underlag.
Utbildningens innehåll
Studiernas upplägg
Ansökan och viktiga datum
- Utbildningen startar
- Utbildningen slutar
Lön och lönefördelning
Vanliga yrken efter utbildningen
Studenterna
Geografisk bakgrund
Tidigare gymnasieskolor och program
Genomströmning och utfall
Om anordnaren
Källor och datakvalitet
Utbildningsfakta för valt tillfälle kommer från Skolverket Susa-navet.
Hämtad . Publicerad . Tider visas i svensk tid.
Källidentitet och publiceringsversion
- Publiceringsversion
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Utbildningsidentitet hos källan
- i.uoh.lu.naber.18173.20262
- Tillfällesidentitet hos källan
- e.uoh.lu.naber.18173.20262
- Utbildningsformens källkod
- HS
- Utbildningskod hos källan
- NABER
- Ändringstid enligt källan
- 2026-02-10T09:47:30
Anordnare, utbildning och utbildningstillfälle är separata identiteter. Uppgifter om ansökan bör kontrolleras på den officiella webbplatsen. Kompletterande statistik har inte hämtats från denna källa.