Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analysing high-throughput molecular biological and sequence data, and interpret the obtained results.
This interdisciplinary two-year programme focuses on acquiring
- basic background knowledge in diverse disciplines belonging to the field of bioinformatics, including statistics, molecular biology and computer science - expert knowledge in the field of bioinformatics - programming skills - engineering skills
The 120-credit programme consists of a reorientation package (one semester), a common package (two semesters) and a major.
This is an initial Master's programme and can be followed on a full-time or part-time basis.
Learning outcomes Master of Bioinformatics
The student 1 Possesses a broad knowledge of the principles of genetics, biochemistry and molecular and cellular biology that underlie the model systems, the experimental techniques, and the generation of data that are analyzed and modeled in bioinformatics.
2 Possesses a broad knowledge of the basic mathematical disciplines (linear algebra, calculus, dynamical systems) that underlie mathematical and statistical modeling in bioinformatics.
3 Masters the concepts and techniques from information technology (database management, structured and object-oriented programming, semantic web technology) for the management and analysis of large amounts of complex and distributed biological and biomedical data.
4 Masters the concepts and techniques from machine learning and frequentist and Bayesian statistics that are used to analyze and model complex omics data.
5 Has acquired knowledge of the core methods of computational biology (such as sequence analysis, phylogenetic analysis, quantitative genetics, protein modeling, array analysis).
6 Has advanced interdisciplinary skills to communicate with experts in life sciences, applied mathematics, statistics, and computer science to formalize complex biological problems into appropriate data management and data analysis strategies.
7 Can - in collaboration with these experts - design complex omics experiments and analyze them independently.
8 Can independently collect and manage data from specialized literature and public databases and critically analyze and interpret this data to solve complex research questions, as well as develop tools to support these processes.
9 Investigates and understands interaction with other relevant science domains and integrate them within the context of more advanced ideas and practical applications and problem solving.
10 Demonstrates critical consideration of and reflection on known and new theories, models or interpretation within the specialty; and can efficiently adapt to the rapid evolution the life sciences, and especially in omics techniques, by quickly learning or developing new analysis strategies and incorporating them into the learned competences.
11 Presents personal research, thoughts, ideas, and opinions of proposals within professional activities in a suitable way, both written and orally, to peers and to a general public.
12 Develop and execute original scientific research and/or apply innovative ideas within research units.
Bioinformaticians find careers in the life sciences domain in the broadest sense: industry, the academic world, health care, etc. The expanding need for bioinformatics in biological and medical research ensures a large variety of job opportunities in fundamental and applied research. 60% of our graduates start a PhD after graduation.
Recipient: KU Leuven
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