Bio Data Science

  • Abschluss Master of Science
  • Dauer 4 Semester
  • Art Berufsbegleitendes Präsenzstudium

The economic benefit of combining bioanalytics and bioinformatics for data generation and data analysis is no longer a vision of the future.

There is a wide field of possibilities for discovering new contexts and thus contributing to the understanding of the "Big Picture". This requires interdisciplinary know-how, the best possible technical equipment and a pool of competent scientists.

With the new extra-occupational master program "Bio Data Science" in Tulln you learn to manage the growing flood of data in the laboratory, from genomics to metabolomics, from sampling to interpretation of the data.

The University of Applied Sciences has six laboratories for bioanalytical data generation and the corresponding hardware and software for data evaluation, including state-of-the-art equipment for the various omics areas. These are used for research and commissioned analyses as well as for teaching.


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Überblick über den Studiengang


Organisational Form

Per Semester:

  • Mondays and Wednesdays (17:30 - 21:00)
  • 7 Fridays starting at 14:00 and 7 Saturdays (full-time)
  • 5 additional lab days (working days)

Distance learning and blended learning, as well as the interactive design of courses with modern didactic methods, lead to effective knowledge transfer and high learning efficiency.

In the 3rd semester in the context of a case study, an experiment focused on current research topics (e.g. in the fields of metabolomics or metagenomics) is planned and performed.

Within the Research Proposal, a scientific question for the Master's Thesis is independently derived and discussed - the final step in optimally preparing for the Master's Thesis in the 4th semester. The Master´s Thesis can also be carried out at an employer for suitable subject-specific topics.


General bioanalytics

  • Independent scientific work in an interdisciplinary research environment
  • Statistical planning, generation of bioanalytical data in the laboratory and evaluation
  • Revealing biologically relevant and significant relationships
  • On-line and in-line process analytics
  • Best practice of bioinformatic data analysis
  • Pathway analysis

Genomics / Transcriptomics

  • State-of-the-art techniques for sequencing biomolecules (NGS)
  • Quality assessment of functional genomics datasets
  • Identifying biologically relevant signals, interpreting them biologically and deriving biomarkers
  • Bioinformatics methods for metagenomic data analysis

Metabolomics / Proteomics

  • Applying advanced strategies and software tools to analyze metabolomics and proteomics datasets for biological relevance and significance
  • Metabolic simulations
  • Combination of various omics disciplines


Zugangsvoraussetzungen & Studiengebühren

  • Preliminary studies in natural sciences, engineering or health sciences
  • Visit to a one-week summer school free of charge, working in high-tech laboratories of the FH to enable optimal preparation for the master's program.

Tuition fee: 363,36 € per semester + ÖH-fee


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Bio Data Science (english)