Program Overview

MSc Scientific Computing with Data Science

Overview

This programme is designed for recent graduates in Physical or Life Sciences who wish to learn more about computing and its applications in advancing scientific research. The programme will help students develop skills in coding, machine learning, and high-performance computing, and apply these skills 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. The programme will train students in coding and data science, building on their core scientific knowledge and giving them a robust appreciation of what can be achieved by combining these skills.

Key Information

• Programme duration: One year full-time
• Start date: September 2025
• Application deadline:
  • Overseas applicants: 25 July 2025
  • Home applicants: 8 August 2025
• Delivery method: On-Campus
• Location: Clifton
• Awards available: MSc

Programme Structure

This programme will admit students with any scientific background. Prior computing experience is useful but not essential; students will be streamed according to their computing knowledge to bring everyone to the same level at the end of their initial coding course.

Students will take 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, machine learning, and artificial intelligence
• Use of cloud technologies
• Data visualisation
• Numerical methods

In addition, students will take a 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 their qualifications and timetabling).

To complete their studies, students will carry out an individual research project, which they can choose from a selection proposed by project supervisors. This project will provide students with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work, applying their computing skills to a cutting-edge challenge in 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.

Students 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 students 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 include:

• 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 students are currently completing a degree, the university understands that their final grade may be higher than the interim grades or module/unit grades they have achieved during their studies to date.

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

The university will also consider applications if the final overall achieved grade is slightly lower than the programme's entry requirement. If students have at least one of the following, they should include their CV (curriculum vitae/résumé) when they apply, showing details of their relevant qualifications:

• Evidence of relevant work experience working at solving scientific problems or as technicians in the Chemical, Bioscience, Physics (e.g., 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.

Fees and Funding

• Home: full-time: £16,600 per year
• Overseas: full-time: £37,500 per year

Fees are subject to an annual review. For programmes that last longer than one year, students should budget for up to an 8% increase in fees each year.

Career Prospects

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, students will develop a strong foundation in how to apply modern computing to solve problems in science, providing them with an edge in a competitive and fast-changing labour market.

In addition, project work provides students 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 focused 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.