MSc Scientific Computing with Data Science
Are you a recent graduate in a Physical or Life Science who would like to learn more about computing and how it is applied to advance scientific research? This programme will help you achieve your goals. Schools in the Faculty of Science are all ranked in the top 5 for research in the UK (THE analysis of REF 2021) and Bristol is ranked in the top ten in the UK for Natural Sciences (QS 2023). Develop your skills in coding, machine learning and high-performance computing and learn how to apply these to cutting-edge computational problems drawn from across the sciences.
Scientific computing is an interdisciplinary field that uses computer science, data science and digital technology to solve problems across a wide range of subject areas, including maths, engineering, biology, physics, chemistry, geography and earth sciences. Whatever your scientific background, this programme will train you in coding and data science, building on your core scientific knowledge and giving you a robust appreciation of what can be achieved by combining these skills.
You will master modern programming languages, data science and machine learning algorithms, and apply them to problems in your chosen science. You will understand the main software engineering concepts and principles involved in scientific computing and data science and use them to model complex scientific systems, giving you an edge in a competitive and fast-changing labour market. Through project work, industrial networking and visits, you will have opportunities to build contacts, opening up additional job opportunities once qualified.
Most of your core teaching will be delivered by academics linked to Bristol Scientific Computing (BriSC), who are based in the Faculty of Science. BriSC brings together experts from across the University whose teaching and research focus on applying the latest computational techniques to key scientific problems, such as changes in the earth's atmosphere, the reactions of molecules or how galaxies are formed. The learning of programming languages and computational techniques is most effective when it is practice-based. Therefore, the computing units in this programme are mainly delivered through interactive workshops and student-led activities, supported by seminars and tutorials.
The MSc in Scientific Computing with Data Science builds on the University of Bristol's unique strengths and facilities as a world-class centre for supercomputing, data science and data-intensive research.
This programme will admit students with any scientific background. Prior computing experience is useful but not essential; you will be streamed according to your computing knowledge to bring everyone to the same level at the end of your initial coding course.
You will take 80 credit points of compulsory units covering:
- Scientific programming using modern interpreted and compiled languages
- Research software engineering best practice, including version control, modern programming environments and testing
- Data analysis methods including data manipulation and cleaning, regression and machine learning
- Data visualisation
- Numerical methods
In addition, you will take a 20 credit point group project, applying coding and data analysis to problems set by industrial and academic partners, as well as choosing additional credits from a range of final year options from our undergraduate programmes (depending on your qualifications and timetabling).
To complete your studies, you will carry out a 60 credit point individual research project, which you can choose from a selection proposed by project supervisors. This project will provide you with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work, applying your computing skills to a cutting-edge challenge in science.
Visit our programme catalogue for full details of the structure and unit content for our MSc in Scientific Computing with Data Science.
This course is intended for Physical/Life Science graduates, unfortunately we cannot consider applicants with Computer Science degrees for this programme.
An upper second class honours degree (or international equivalent) in Natural/Physical Sciences (e.g. Chemistry, Physics, Earth Science, Geology, Geographical Sciences, Environmental Sciences). Degrees in Life Sciences (e.g. Biochemistry, Pharmacology, Molecular Biology, Computational Biology, Biophysics, Cell biology, Molecular biology, Physiology, Anatomy, Zoology, Plant sciences, Neuroscience, Psychology, Virology, Microbiology, Immunology, Medicine) will need to demonstrate competency in Maths with at least one undergraduate Maths module at 2.1 or above. Engineering or Mathematics and Statistics degrees will also be considered if applicants have a minimum of 5 science modules at 2.1 or above. Computing experience is not essential.
For applicants who are currently completing a degree, we understand that their final grade may be higher than the interim grades or module/unit grades they achieve during their studies.
We will consider applicants whose interim grades are currently slightly lower than the programme's entry requirements. We may make these applicants an aspirational offer. This offer would be at the standard level, so the applicant would need to achieve the standard entry requirements by the end of their degree. Specific module requirements may still apply.
We will consider applicants whose grades are slightly lower than the programme's entry requirements, if they have at least one of the following:
- evidence of significant, relevant work experience with minimum of 6 months working at solving scientific problems or as a technician.
- a relevant postgraduate qualification.
If this is the case, applicants should include their CV (curriculum vitae / résumé) when they apply, showing details of their relevant work experience and/or qualifications.
See international equivalent qualifications on the International Office website.
Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.Go to admissions statement
Fees and funding
- UK: full-time
- £15,100 per year
- Overseas: full-time
- £34,100 per year
Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to an 8% increase in fees each year.
More about tuition fees, living costs and financial support.
This MSc provides graduates with the skills needed for successful careers in computing, data analysis and scientific research in private and public sector roles. Through interactive workshops and project work, you will develop a strong foundation in how to apply modern computing to solve problems in science, providing you with an edge in a competitive and fast-changing labour market. In addition, project work provides you with an opportunity to build contacts, with the potential to open up additional career opportunities once qualified. This will be supported by opportunities for networking with industrial users of scientific computing through lectures, visits and, where appropriate, projects. This will be an intense and focussed programme for experienced learners. Projects provide extensive opportunities to develop skills in communication, presentations, technical writing, project management and group work, as well as developing networking skills and industry contacts.