Master program

Our group is one of the leading education groups within the Bioinformatics and Biocomplexity master program. Many of the courses offered by this master program are given by the members of our group. After following compulsory courses, students enrolled in this master can perform original research in our group with a focus on modelling and/or bioinformatics.. Since our research is addressing current questions in biology, a solid understanding of the relevant biology is required.

Additionally, we have research projects available for students doing the Bioinformatics profile. Note that you have to choose the 45 EC variant where a research project of 33 EC is included.

Excellent students in the Bioinformatics and Biocomplexity master programme are advised to follow the QBio honours programme with a special focus on quantitative biology.

Every PI in our group has their own research line. Below we give a short list of possible research fields where master students can perform their research project. Please check out our Research page for an overview of the research done at the TBB group.

A full list of MSc courses that our group is participating can be found in here.

Possible Research projects

Our aim is to develop computational models that enriches our mechanistic understanding of complex living systems at all scales, e.g., from molecules to cells, to organisms (or patients), and communities (or ecosystems). Research projects in the master program revolve around the main research lines of the group:

• Developmental biology: Simulate multi-scale computational models to study complex developmental pattern formation processes and their evolution.
• Quantitative Immunology: Analyse and model immunological data to improve our understanding of the functioning of the immune system in a quantitative manner.
• Evolutionary Genomics: to compare genome sequences and integrate highthrougput data sets.
• Multilevel evolution: To understand how different levels of selection, complex genotype phenotype mapping, and interactions over different timescales contribute to the evolution of complexity at the level of individuals and/or ecosystems.
• Evolution in heterogeneous environments: How do environmental heterogeneities in biotic and abiotic factors affect evolutionary adaptation?
• Bacterial physiology: Bacterial cells can change their composition dramatically upon a change of environment. What logic governs these adaptations?
• Metagenomics: Metagenomics is the sequencing of genetic material directly from an environment. Countless new microbes and viruses are readily discovered, and we investigate their identity and role in the ecosystem. Our goal is a full understanding of metagenomic datasets based on bioinformatic data analysis and computational modelling.
• Fungal Evolutionary Genomics Group: The Fungal Evolutionary Genomics group uses comparative genomics approaches complemented by wet lab experiments to understand genome evolution and function, and how fungi adapt to novel or altered environments, both on short and long evolutionary timescales.
• Immunological Bioinformatics: The development of several data driven computational methods to predict which parts of pathogenic microorganisms but also tumors generate an immune response.