MSc in Bioinformatics and Computational Biology

Key Points

  • Work permit while you study

  • Post Graduation Work Permit for 24 months

  • Start dates: September

  • Duration: 1 year

  • Level 9 qualification

  • Type: Full Time
  • Hours: Daytime
  • Tuition Fee: From 18,130 € / year

Write to us for more information

Bioinformatics is a rapidly growing field at the intersection of biology, mathematics, and computer science. It seeks to create, advance and apply computer / software based solutions to solve formal and practical problems arising from the management and analysis of very large biological data sets. Applications include analysis of genome sequence such as the human genome, human microbiome, analysis of genetic variation within populations, and analysis of gene expression patterns.

Program description

The master’s program will train participants at an advanced level in bioinformatics theory and applications. Graduates of the program:

  • They will have a solid background in the theory behind bioinformatics methods and tools so that they can critically evaluate bioinformatics research .
  • They will be able to use existing bioinformatics methods and tools and quickly learn to apply new methods and tools.
  • They will be able to organize, process and analyze large data sets generated by systems biology and genomics approaches.
  • They will be able to program and create scripts to analyze various biological data formats within a command line computing environment.
  • They will understand the role of modeling and simulation of biological systems.
  • They will have a deep understanding of the aspect of bioinformatics in which they carried out their three-month research project (such as part of the master’s program). This experience will prepare them for a future research career in the field of bioinformatics.

Career options

Working in the bioinformatics field is challenging and satisfying work, often involving problem solving, programming, statistical analysis of large data sets, and mathematical modeling of biological phenomena . It is possible for a bioinformatician to work on many different biological questions and types of data sets, making this an interesting and exciting field to work on.

The daily work of a bioinformatician may involve studying different fascinating and important biological questions, such as:

  • How many genes are in the human genome and can we identify them all?
  • What are the differences in the DNA of different people and how does this affect their health, appearance and behavior?
  • Is it possible to create a computer program to analyze the DNA sequences of 1000 different individual humans and reconstruct their genetic history ?
  • What are the differences between cancer cells and healthy cells?
  • How do new drug-resistant strains of malaria evolve from existing strains and can we predict which strains will emerge? in the future?
  • What bacteria are present in different environments, such as different parts of the human body in people of different ages, populations, and health ?
  • How are different groups of animals related to each other (eg, humans, flies, jellyfish, earthworms? , etc.), and when and where did they evolve from a common ancestor?
  • And many other interesting and important questions

Program structure

The master’s program has four different streams: for graduates in biology, mathematics, statistics, and computer science, respectively.

Students are required to complete 12 modules and undertake a research project. Each module consists of approximately 20 one-hour lectures (approximately two lectures per week during an academic period), as well as approximately 10 hours of practicals or tutorials (approximately one hour-long practical or tutorial per week during an academic period), although the exact number of lectures, labs, and tutorials varies between individual modules.

  • Mathematical modeling for biological and environmental sciences (5 credits)
  • Open source infrastructure for modeling and Big Data (5 credits)
  • Introduction to relational databases (5 credits)
  • Data mining (5 credits)
  • Programming for bioscientists I (5 credits)
  • Programming for bioscientists II (5 credits)
  • Computational systems biology (5 credits)
  • Genomic data analysis (5 credits)
  • Thesis in Bioinformatics and Computational Biology (30 credits)
  • Discrete Mathematics (5 credits)
  • Data Analysis I (5 credits)
  • Data Analysis II (5 credits)
  • Introduction to Probability and Statistics (5 credits)
  • Introduction to probability and statistics (5 credits)
  • Molecular biology (5 credits)
  • Biomolecules (5 credits)
  • Cells, biomolecules, genetics and evolution (5 credits)
  • Data mining (5 credits)
  • Programming for bioscientists I (5 credits)
  • Programming for bioscientists II (5 credits)
  • Computational systems biology (5 credits)
  • Genomic data analysis (5 credits)
  • Dissertation in Bioinformatics and Computational Biology (30 credits)
  • Discrete Mathematics (5 credits)
  • Data Analysis I (5 credits)
  • Data Analysis II (5 credits)
  • Choice of: Data analysis I (5 credits) or Data analysis II (5 credits)
  • Mathematical modeling for biological and environmental sciences (5 credits)
  • Molecular biology (5 credits)
  • Biomolecules (5 credits)
  • Cells, biomolecules, genetics and evolution (5 credits)
  • Open source infrastructure for modeling and Big Data (5 credits)
  • Data mining (5 credits)
  • Programming for bioscientists I (5 credits)
  • Programming for bioscientists II (5 credits)
  • Introduction to relational databases (5 credits)
  • Computational systems biology (5 credits)
  • Genomic data analysis (5 credits)

Dissertation in Bioinformatics and Computational Biology (30 credits)

  • Mathematical modeling for biological and environmental sciences (5 credits)
  • Molecular biology (5 credits)
  • Biomolecules (5 credits)
  • Cells, biomolecules, genetics and evolution (5 credits)
  • Open Source infrastructure for modeling and Big Data (5 credits)
  • Introduction to relational databases (5 credits)
  • Data mining (5 credits)
  • Programming for bioscientists I (5 credits)
  • Programming for bioscientists II (5 credits)
  • Computational Systems Biology (5 credits)
  • Genomic Data Analysis (5 credits)
  • Dissertation in Bioinformatics and Computational Biology (30 credits)
  • Discrete Mathematics (5 credits)

Admission requirements

  • Program participants must hold a Bachelor’s degree with honors, or an equivalent qualification, in a discipline with a significant element of mathematics, statistics, engineering, computer science, or biology, with a minimum of second grade with class 1 honors.
  • For international candidates, the foreign equivalent is required. In addition, an officially translated degree will be required.
  • IELTS 6.5, with no less than 6 in any component (or its internationally recognized equivalent).

* It is not necessary to have previous knowledge of computer programming or bioinformatics to take the course. All necessary computer skills will be taught as part of the program.

Learn more about our educational offer

Request your quote

An advisor will contact you by phone and email within the following hours