Scientific Computing with Data Science

Entry requirements

This course is intended for Physical/Life Science graduates. Unfortunately, applicants with a Computer Science degree are not suitable for this programme.

You will typically need an upper second-class honours degree or international equivalent in:

Natural/Physical Sciences:

• Chemistry
• Earth Science
• Environmental Sciences
• Geographical Sciences
• Geology
• Physics

The below Life Science degrees will be considered if you can demonstrate competency in Maths with at least one undergraduate Maths module at 60% (or international equivalent) or above. :

• Anatomy
• Biochemistry
• Biophysics
• Cell biology
• Computational Biology
• Immunology
• Medicine
• Microbiology
• Molecular Biology
• Neuroscience
• Pharmacology
• Physiology
• Plant sciences
• Psychology
• Virology
• Zoology

Examples of Maths modules at 60% (or international equivalent) or above includes:

• Data Mining/Data Science/ Data Analytics
• Mathematics
• Mathematical Methods
• Mathematics for Science
• Probability
• Quantitative Chemistry
• Quantitative Methods
• Quantitative Research Methods
• Statistics/Statistical Methods/Statistical Analysis, etc

Engineering, Mathematics and Statistics degrees will also be considered if applicants have a minimum of four science modules at 60% (or international equivalent) or above. Examples of modules include:

• Applied Mathematics
• Applied Solid Mechanics
• Biology
• Biomedical Engineering
• Biosciences
• Biomaterials
• Battery Technology
• Chemistry
• Chemical Engineering
• Composites and Ceramics
• Computational Fluid Dynamics
• Engineering Science
• Environmental Engineering
• Epidemiological Methods
• Fluid Mechanics and Heat Transfer
• Fuels and Sustainability
• Physics
• Physical Materials Science
• Polymers
• Renewable Energy for a Sustainable Future
• Statistical and Molecular Epidemiology
• Structures and Materials
• Sustainability
• Solar Energy Engineering

Computing experience is not essential.

If you are currently completing a degree, we understand that your final grade may be higher than the interim grades or module/unit grades you have achieved during your studies to date.

We will consider your application if your interim grades are currently slightly lower than the programme's entry requirements and may make you an aspirational offer. This offer would be at the standard level, so you would need to achieve the standard entry requirements by the end of your degree. Specific module requirements would still apply.

We will also consider your application if your final overall achieved grade is slightly lower than the programme's entry requirement. If you have at least one of the following, please include your CV (curriculum vitae / résumé) when you apply, showing details of your relevant qualifications:

• evidence of relevant work experience working at solving scientific problems or as technicians in the Chemical, Bioscience, Physics (eg CERN, Diamond etc) industries (minimum six months paid, full or part-time).
• a relevant postgraduate qualification from the accepted subjects listed above.

Specific module requirements would still apply.

See international equivalent qualifications on the International Office website.

Months of entry

September

Course content

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 2024). 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.

Information for international students

See international equivalent qualifications on the International Office website.

Fees and funding

Further information on funding for prospective UK and international postgraduate students.