Master's degree in Bioinformatics Back
The two-year Master’s degree programme in bioinformatics at the University of Aarhus targets students from tertiary education institutions in Denmark and abroad. The degree programme is both practical and research-oriented and is aimed at the business community, research institutions and the public sector.
The degree programme is also flexible and shaped to match your academic interests, and you can therefore specialise in a bioinformatics topic while at the same time acquiring general competences in bioinformatics. You do not need to have knowledge of the Danish language before commencing the degree programme. At the University of Aarhus, the teaching is in English unless all participants speak Danish. The teaching at the university is greatly influenced by the research conducted here, as the teachers are active researchers.
As a Master’s degree student, you have excellent opportunities for working with researchers and you can also complete a project in collaboration with a private company. The Master’s thesis written during the last year of the degree programme carries considerable weight and, in this context, you benefit from the down-to-earth, informal atmosphere between staff and students. When you write your thesis, you have excellent opportunities for being associated with a group of researchers. In this way, you can participate in the group’s research projects, academic discussions and articles.
You can specialise in a topic within a broad area, including one of the three areas of bioinformatics in which the University of Aarhus has particular strength: Evolutionary bioinformatics (e.g. association mapping and genome analysis). Structural bioinformatics (e.g. molecular docking). Medical bioinformatics (e.g. pathway and network analysis as well as microarray analysis).
Masters - Full time
- Start date:
- 2 Years
- Teaching method:
- Århus, Denmark
- EUR 13,500.00
- EUR 13,500.00
- Tuition fees
|Module name||Credits (ECTS or CATS)||Duration||Core / elective / recommended||Available as Short course (CPD)|
|Artificial Neural Networks|
|Classification and Regression Problems|
|Indirect Effects of Selection|
|Localisation and Identification of Genes Causing Disease|
|Modelling Dynamic Systems|
|Molecular Population Genetics|
|Random Genetic Drift|