University of Helsinki

Life Science Informatics, M.Sc.

  • Application Deadline
  • 24 months
    Duration
  • Tuition
    15000
    Tuition (Year)
    Free
    Tuition (Year)
  • English, Finnish, Swedish
    Language
Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE). As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. This course is delivered at University of Helsinki.
  • Overview
  • Programme outline
  • Key facts
  • Admission requirements
  • Fees and funding

About

The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The Life Science Informatics programme from University of Helsinki is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics. As a graduate of the LSI programme you will:

  • Have first class knowledge and capabilities for a career in life science research and in expert duties in the public and private sectors
  • Competence to work as a member of a group of experts
  • Have understanding of the regulatory and ethical aspects of scientific research
  • Have excellent communication and interpersonal skills for employment in an international and interdisciplinary professional setting
  • Understand the general principles of mathematical modelling, computational, probabilistic and statistical analysis of biological data, and be an expert in one specific specialisation area of the LSI programme
  • Understand the logical reasoning behind experimental sciences and be able to critically assess research-based information
  • Have mastered scientific research, making systematic use of investigation or experimentation to discover new knowledge
  • Have the ability to report results in a clear and understandable manner for different target groups
  • Have good opportunities to continue your studies for a doctoral degree

Career

The Master of Life Science Informatics degree provides excellent opportunities to apply and perform postgraduate studies either at the University of Helsinki, at other universities in Finland, or abroad. As a graduate, you might also find employment, for example, in health sector enterprises, such as bioindustry.

Programme Structure

The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.
  • Algorithmic bioinformatics with the Genome-scale algorithmics, Combinatorial Pattern Matching, and Practical Algorithms and Data Structures on Strings research groups. This specialisation area educates you to be an algorithm expert who can turn biological questions into appropriate challenges for computational data analysis. In addition to the tailored algorithm studies for analysing molecular biology measurement data, the curriculum includes general algorithm and machine learning studies offered by the Master's Programmes in Computer Science and Data Science.
  • Applied bioinformatics, jointly with The Institute of Biotechnology and genetics.Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.
  • Biomathematics with the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group.
  • Biostatistics and bioinformatics is offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational Genetics, Computational Genomics and Computational Systems Medicine in FIMM. Topics and themes include statistical, especially Bayesian methodologies for the life sciences, with research focusing on modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of collaborative topics in various biomedical disciplines. In particular, research and teaching address questions of population genetics, phylogenetic inference, genome-wide association studies and epidemiology of complex diseases.
  • Eco-evolutionary Informatics with ecology and evolutionary biology, in which several researchers and teachers have a background in mathematics, statistics and computer science. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Evolutionary biology studies processes supporting biodiversity on different levels from genes to populations and ecosystems. These sciences have a key role in responding to global environmental challenges. Mathematical and statistical modelling, computer science and bioinformatics have an important role in research and teaching.
  • Systems biology and medicine with the Genome-scale Biology Research Program in Biomedicum. The focus is to understand and find effective means to overcome drug resistance in cancers. The approach is to use systems biology, i.e., integration of large and complex molecular and clinical data (big data) from cancer patients with computational methods and wet lab experiments, to identify efficient patient-specific therapeutic targets. Particular interest is focused on developing and applying machine learning based methods that enable integration of various types of molecular data (DNA, RNA, proteomics, etc.) to clinical information.

Detailed Programme Facts

  • Full-time duration 24 months
  • Study intensity Full-time
  • Credits
    120 ECTS
  • Languages
    • English
    • Finnish
    • Swedish
  • Delivery mode
    On Campus
  • More information Go To The Course Website
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Eligibility

  • You demonstrate by 31 July that you have completed a first- or second-cycle degree or a postgraduate degree in Finland or abroad.
  • You demonstrate by 12 January that you have completed the studies required for the programme.
  • You demonstrate by 12 January that you are proficient in English in the manner specified in Rector’s Decision.

Application documents

  • Copy of degree certificate
  • Official transcript of records
  • Certificate of language skills
  • Authorised translations into Finnish, Swedish or English
  • Motivation letter and study plan

Tuition Fee Per Year

  • EUR 15000 International
  • Free EU/EEA

Funding

Check the programme website for information about funding options.

StudyPortals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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