About Bioinformatics, MRes, MSc, PG Dip, Postgraduate Certificate - at University of Exeter
Bioinformatics encompasses all aspects of biological information acquisition, processing, storage, distribution, analysis and interpretation. This programme provides an overview of current developments and introduces appropriate and novel tools and techniques from computer science, biology and mathematical statistics. The programmer also addresses the current uses of bioinformatics in biotechnology, ethical issues and the use of future technologies for bioinformatics research. In addition, the research project gives you an opportunity to undertake a substantial, individually motivated and practically oriented piece of work, which allows you to apply your knowledge in real biological domains.
All modules are ‘blocked’ into short, intensive four-week periods, thereby allowing credit to be accumulated through short-period placements of four weeks by students from industry wishing to update their knowledge and skills base.
All material is specifically designed for Masters level and will form an ideal grounding for your future career. The programme has a significant research component, which accounts for about half of the programme, as well as professional skills training, and is designed to provide training in areas most relevant for your academic and professional development.
Distance learning We also offer a distance learning variant of the programme, aimed at international students and those already in industry who wish to retrain in bioinformatics. Please see the MSc in Bioinformatics by Distance Learning page.
Entry requirements The course is designed to accommodate postgraduate students from a wide range of first-degree backgrounds. You will require at least a 2:2 degree or equivalent in any scientific or engineering discipline, including natural, mathematical and cognitive science or, if you are a graduate in non-scientific disciplines, you will have at least a 2:1 and your degree must have contained a significant computational or empirical component, e.g. programming, experimental design, data analysis, or project.
