Computational Mathematics BSc
Study of mathematics, programming, and data to solve complex real-world problems.
Is this for you?
This degree could suit you if you:
Enjoy maths and computing
Like solving complex problems
Are analytical
Want a tech or research career
Are detail-focused
Popular Career Fields
Finance & Banking
Research & Academia
Technology & Startups
Consulting
Your Personality Might Be:
Mathematically strong
Research & Academia
Problem-solver
Logical thinker
What is it?
What Is a Computational Mathematics Degree?
Computational Mathematics combines mathematics, computer science, and data analysis to model, simulate, and solve real-world problems. It focuses on how mathematics and computing work together to understand everything from climate change to financial systems.
Why Study Computational Mathematics?
If you enjoy both maths and technology, this degree lets you use logic and programming to tackle practical challenges. You’ll learn how to create mathematical models, write algorithms, and analyse data - skills that are essential in science, engineering, and finance.
Course Summary
Study of mathematics, programming, and data to solve complex real-world problems.
What you'll study
Most Computational Mathematics degrees cover:
Calculus, algebra, and statistics
Numerical analysis and mathematical modelling
Programming and algorithms
Data science and machine learning
Scientific computing and simulation
Optimisation and operations research
Later in your course, you can usually specialise - for example, in finance, artificial intelligence, physics, or data analytics.
Degree Types
BSc (Bachelor of Science): Focuses on mathematical techniques, programming, and applied computation.
MSci or Integrated Master’s: A four-year degree offering deeper study and research in computational methods.
Skills You'll Gain
A Computational Mathematics degree builds both analytical and practical skills, which might include:
Numerical Modelling – using numerical methods to solve complex mathematical and scientific problems.
Algorithm Development – designing efficient computational algorithms for simulations and calculations.
Programming Skills – coding in languages like Python, MATLAB, C++, or R for mathematical computing.
Data & Statistical Analysis – interpreting datasets using mathematical and computational techniques.
Applied Problem-Solving – using maths and computation to model real-world systems and optimise solutions.
Explore Uni Open Days
Pathways, Placements and Work Experience
CAREERS
Career Pathways
Graduates in Computational Mathematics are in demand across many sectors, including:
Finance and data analytics
Engineering and scientific research
Software and technology
Energy and environmental modelling
Government and policy analysis
Other pathways include postgraduate study in applied mathematics, computing, or data science. Career options are broad and growing as data and modelling become central to innovation.
Work Experiences & Placements
Many universities offer:
Industry placements or sandwich years, often with technology, engineering, or finance companies.
Summer internships in data analysis, modelling, or research.
These experiences help you apply mathematical and computing skills in real settings and prepare for graduate roles.
Salary Profile
Coming soon
Qualifications, Personal Satement, What to do Next?
AM I ELIGIBLE?
Entry Requirements
A-levels or equivalent including Maths. Further Maths is highly beneficial. Computer Science, Physics, or Computing are also beneficial.
Personal Statement Tips
Show your enthusiasm for both maths and computing.
Mention coding, maths, or modelling projects you’ve completed.
Explain how you enjoy solving real-world problems using logic and numbers.
Highlight any extra learning, such as online coding or data courses.
What to do Next
Compare degree options to see which balance of maths and computing suits you.
Attend open days or virtual events to explore labs and meet lecturers.
Try online programming or data analysis tutorials.
Explore how maths and computing power industries like climate science, finance, and AI.
Wider Reading
Weapons of Math Destruction by Cathy O’Neil – How data and algorithms affect everyday life.
How Not to Be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg – A fun look at how maths explains the world.
The Art of Statistics by David Spiegelhalter – How to make sense of data and uncertainty.
Algorithms to Live By by Brian Christian and Tom Griffiths – How mathematical thinking helps solve human problems.