Master of Science in Bioinformatics: Engineering
With a bachelor degree in Engineering or Computer Science, you have the optimal background to become a bioinformatics engineer.
As bioinformatics engineer, you are skilled in developing new algorithms and complex software implementations, primarily focusing on, but equally applicable outside the bioinformatics domain. You will follow a module of ‘biologically oriented’ courses (9 credits) that will provide you with the basic domain knowledge to understand a data-driven biological problem. However, the major part of your curriculum (engineering module of 42 credits) will focus on advanced engineering and computer science techniques that elaborate on an already advanced knowledge obtained during your bachelor. The applied bioinformatics module (33 credits) will make you familiar with the data specificities of the bioinformatics domain (preprocessing techniques, noise and potential biases, assumptions etc.) and allow you to acquire the essential interdisciplinary skill set that is needed to be successful in modern science and engineering. The master thesis corresponds to 30 credits and focuses on a research topic. Within your programme, you have the opportunity to do an internship in order to become familiar with the role and expectations of a bioinformatics engineer in the industry or a governmental institution.
Master of Science in Bioinformatics: Systems Biology / Master of Science in Bioinformatics: Bioscience Engineering
With a bachelor degree in Biochemistry and Molecular Biology or in Bioscience Engineering, you can decide to become a bioinformatics scientist/bioengineer. A bioinformatics scientists applies (bio)informatics tools and techniques to understand a biological system or to solve an innovative research question. You are trained as a problem solver who can creatively and efficiently combine bioinformatics tools and algorithms to analyse, integrate and model data. Having the essential programming and data analysis skills requires a deep understanding of statistics, programming and data analytical techniques (applied mathematics and informatics module of 21 credits). The applied bioinformatics module (33 credits) will make you familiar with the basic data analytical methods (e.g. NGS analysis), help you to acquire interdisciplinary skill sets and illustrate how theoretical concepts of statistics and data mining are used to build bioinformatics tools.
The difference between the Bioscience Engineering and the Systems Biology track is that the former deepens the engineering skills (Bioscience Engineering track of 27 credits), whereas the Systems Biology track (30 credits) pays more attention to advanced (systems) biological knowledge. The master thesis corresponds to 30 credits and focuses on a research topic. Within your programme, you have to opportunity to do an internship in order to get familiar with the role and expectations of a bioinformatics scientist in the industry or a governmental institution.
Technological advances have turned biology in a data-driven science. The avalanche of molecular data enables key discoveries in biology, ecology and molecular evolution, drives innovation in biotech and pharma industry and supports medical and governmental decision making. However, the power of using these data for innovation depends on interdisciplinary skills to analyse, integrate and interpret the data. There is thus an urgent need for bioinformatics scientists and engineers with an interdisciplinary mind set. Currently a large discrepancy exists between the exponential increase of biological data (28% each year) and the number of newly educated bioinformaticians (increase of only 5,8%) who typically find a job in agro, biotech and pharma industry, in research and governmental institutes, and in genetic centra and hospitals. Because of their interdisciplinary and analytical skill sets bioinformaticians also find their way in consultancy, in spin offs and in data analytics.