Typical Course Length
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.
Modules include Statistical Concepts, Methods and Tools, Statistical Techniques, Programming for Scientists, Machine Learning, Concepts in Biology, and a Dissertation.
For further information please contact Dr Edel Sherratt (email@example.com)
Twelve months full-time or 24 months part time. The academic year (September to September) is divided into three semesters: September to January; January to June; June to September. The course is available as a postgraduate certificate or diploma and can be taken part-time. Students must contact the department to discuss these options.
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.
The programme comprises 180 credits. There are 120 credits of taught modules completed during Semester 1 and Semester 2. This is followed by a research dissertation (60 credits) in semester 3.
BSc or BA honours degree (High 2:2) in a related subject (such as Biology, Computer Science, Software Engineering or Mathematics) at undergraduate level and an accompanying reference. We will consider applicants with other experience which gives an equivalent basis for entry.
English Language Requirements:
If you have a Bachelor’s degree from a UK University, you do not need to take an English proficiency test.
Non-native English speakers who do not meet this requirement must take a University-recognised test of academic English language proficiency. For further information please see our English Language requirements page.
Please see the tuition fee pages for current tuition fees. Please note that all fees are subject to an annual increase.
Funding opportunities may be available, please check the funding calculator for details.
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.
|Module Name||Module Code||Credit Value|
|Biotechnology For Business||BRM0520||20|
|Frontiers In The Biosciences||BRM4920||20|
|Machine Learning For Intelligent Systems||CSM6420||20|
|Programming For Scientists||CSM0120||20|
|Statistical Concepts, Methods And Tools||MAM5120||20|
|Statistical Techniques For Computational Scientists||MAM5220||20|
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.