Statistics for Computational Biology - MSc

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Aberystwyth University
Start - End
12 Sep
Study Options
Full Time
GBP 8700 - 8700
Fee International
GBP 16700 - 16700

Computational Biology is an area of key strategic interest for interdisciplinary research and for employers in pharmaceuticals, advanced agriculture and in public health. The use of statistics in this area is essential. This new MSc will be run jointly between Mathematics, Computer Science, and Biological Sciences, providing an excellent point of entry to this growing area for graduates in any of the three constituent disciplines.


The scheme is designed to introduce key, practice-based skills in statistics for Computational Biology. You will contribute knowledge to the design of Biological experiments to ensure that appropriate statistical analysis of experimental data is possible.

You will learn how to critically evaluate the application of specific statistical techniques to research problems in Computational Biology and then effectively interpret and report the results of analyses.

This master’s degree is all about computational biology and statistics and will be of interest to students that are looking for the minimum entry-level qualification for many excellent employment opportunities in pharmaceuticals, advanced agriculture and in public health.

The course is a collaboration between the departments of Computer Science, Maths and also the Institute of Biological Environmental and Rural Science. The study scheme will bring the departments together in research-led teaching in these areas and you will benefit from expertise and insight from these highly specialised departments. In the most recent Research Excellence Framework assessment (2014) it was found that 95% of the universities research was of an internationally recognised standard or higher.

Contact Time

Approximately 10-14 hours a week in the first two semesters. During semester three you will arrange your level of contact time with your assigned supervisor.



  • Dissertation (60 credits)
  • Frontiers in the Biosciences (20 credits)
  • Machine Learning for Intelligent Systems (20 credits)
  • Programming for Scientists (20 credits)
  • Statistical Concepts, Methods and Tools (20 credits)
  • Statistical Techniques for Computational Scientists (20 credits)

This degree will suit you:

  • If you already have a background in one of biology, maths or computing and now want training in this exciting interdisciplinary area to enhance your current skills.
  • If you have a high 2:2 degree or higher in a related discipline
  • If you wish to gain academic expertise and practical experience in Computational Biology.
  • If you wish to enter a career in Statistics for Computational Biology with opportunities to work in pharmaceuticals, advanced agriculture and public health.

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