MSc Data Science for Biology
Key Details
- Attendance
- Full Time
- Award
- Degree of Master of Science
- Course Length
- 1 year
- Course Start Date
- September 2025
Why you should choose us
Course Overview
Immerse yourself in bioinformatics and data analysis, guided by world-class researchers at the forefront of their fields.
Biosciences are increasingly dominated by vast amounts of data, which can scale from molecular levels (genomic, transcriptomic, proteomic, or metabolomic data) to ecological and environmental data collected from large populations or communities. The ability to manipulate, analyse, and interpret these data is pivotal to addressing the biological challenges of the 21st century.
Our interdisciplinary MSc Data Science for Biology is designed to equip you with comprehensive knowledge and skills in data mining, bioinformatics, and statistics. You’ll become proficient in the analysis of biological data, learning essential skills such as statistical analysis, data visualisation, and bioinformatics techniques. You'll master the tools required to analyse complex biological data, including Python and R. You’ll also have exciting opportunities to collaborate with industry partners at the Norwich Research Park, such as the Earlham Institute, John Innes Centre, and Quadram Institute.
Here at UEA, you’ll be part of our vibrant research community within the School of Biological Sciences. We take a uniquely integrated approach, connecting biology at all scales - from molecules, genes, and genomes to populations and ecological communities. In the 2021 Research Excellence Framework, 92% of our research was classified as ‘world-leading’ or ‘internationally excellent,’ offering you unparalleled research opportunities.
With UEA's MSc in Data Science for Biology, you're not just getting a degree; you're opening doors to a world of opportunities. You’ll graduate with in-demand skills that will pave the way for rewarding careers in biotech, medicine, and the life sciences. Along with a wealth of knowledge, you’ll gain prestigious connections and significant research experience. This unique combination will give you a substantial competitive edge, placing you ahead of other graduates in your career or further studies.
Study and Modules
Structure
Our MSc Data Science for Biology course is a full-time, one-year taught programme, designed for advanced students and practitioners.
On this course, you’ll study professional skills, data mining, Python, statistics in R and bioinformatics. You’ll also explore how data science is being used to enhance our understanding of biological systems. In addition, you’ll have the option to choose to study either information visualisation, or more advanced statistical modelling in R.
A key element of the course is your dissertation, which is an independent scientific research project. The dissertation will give you the chance to explore a biological topic or work on a problem in depth (which may be with an industry partner), under the supervision of a faculty member.
Compulsory Modules
Optional A Modules
(Credits: 20)Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, the University will endeavour to consult with students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff. In some cases optional modules can have limited places available and so you may be asked to make additional module choices in the event you do not gain a place on your first choice. Where this is the case, the University will inform students.
Teaching and Learning
You’ll have an average of 15 hours of contact time per week with teaching staff, depending on your module choices. This time will be a mix of lectures, seminars, and lab classes. Seminars and lab classes will reinforce and expand on the lecture material.
The course has both theoretical and practical elements, so you’ll get hands-on experience in data mining and statistical software.
Your individual study time (around 25 hours per week) will complement the formal teaching and is an opportunity for you to develop your skills and expertise in data analysis.
Your dissertation will also form a key part of your course, which will involve extensive independent study supported by your supervisor.
Assessment
We have a mixture of individual and group assessments, including written work, presentations, and exams. These combine theoretical understanding with practical application and are designed to test the range of skills and competencies required for the learning outcomes of each module. The balance of assessment types varies according to the module options you choose.
A key feature of our MSc is the dissertation in which you’ll work closely with a faculty member to conceptualise, design and deliver an independent scientific research project. Key to the project is the development of skills in applying data science techniques to biological questions. The dissertation is assessed through a project proposal, dissertation report and presentation.
Entry Requirements
- This course is open to
UK and International fee-paying students. Choose UK or International above to see relevant information. The entry point is in September each year.
- Typical UK Entry Requirements
Degree classification
Bachelors degree - 2.2.
Degree Subject
Biology or a related subject area
- Admissions Policy
Our Admissions Policy applies to the admissions of all postgraduate applicants.
- This course is open to
UK and International fee-paying students. Choose UK or International above to see relevant information. The entry point is in September each year.
- Typical International Entry Requirements
Degree classification
UK Bachelors degree - 2.2 or equivalent
Degree Subject
Biology or a related subject area
- English Foreign Language
Applications from students whose first language is not English are welcome. We require evidence of proficiency in English (including writing, speaking, listening and reading):
-
IELTS: 6.0 overall (minimum 6.0 in Writing and Speaking, and 5.5 in Reading and Listening)
We also accept a number of other English language tests. Review our English Language Equivalencies for a list of example qualifications that we may accept to meet this requirement.
Test dates should be within two years of the course start date.
If you do not meet the English language requirements for this course, INTO UEA offer a variety of English language programmes which are designed to help you develop the required English skills.
-
- Admissions Policy
Our Admissions Policy applies to the admissions of all postgraduate applicants.
Fees and Funding
Tuition fees for the Academic Year 2025/26 are:
-
UK Students: £11,775
-
International Students: £24,500
We estimate living expenses at £1,136 per month.
Further Information on tuition fees can be found here.
Scholarships and Bursaries
The University of East Anglia offers a range of Scholarships; please click the link for eligibility, details of how to apply and closing dates.
Course Related Costs
Please see Additional Course Fees for details of course-related costs.
How to Apply
How to apply
Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.
To apply please use our online application form.
Further information
If you would like to discuss your individual circumstances prior to applying, please do contact us:
Postgraduate Admissions Office
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk
International candidates are also encouraged to access the International Students section of our website.
Employability
After the Course
You’ll graduate ready for a career in data analysis or data science with a focus on the Biological Sciences – an area of rapid growth with exciting avenues for career progression.
Careers
Examples of careers that you could enter include:
- Bioinformatician
- Data scientist
- Data analyst
- Data miner
Discover more on our Careers web pages.