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Computational Mathematics BSc

Study of mathematics, programming, and data to solve complex real-world problems.

YOUR PERSONALITY MIGHT BE:

Mathematically strong

Programming-skilled

Problem-solver

Logical thinker

POPULAR CAREER FIELDS

Finance & Banking

Research & Academia

Technology & Startups

Consulting

Is this for you?

Computational Mathematics BSc

Is this for you?

WHAT IS IT?

Study of mathematics, programming, and data to solve complex real-world problems.

CAREER OPTIONS

CURRENT APPRENTICESHIPS, INTERNSHIPS & WORKPLACES

Internships
Internships
Apprenticeships
Apprenticeships
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Uni Open Days
A Computational Mathematics student at work on a computer analysing data.

FIND OUT MORE

About the Course

  • 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.

  • 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.

  • 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.

  • A-levels or equivalent including Maths. Further Maths is highly beneficial. Computer Science, Physics, or Computing are also beneficial.


    • 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.

    • 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.

    • 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.

    • Data Science - Data scientist, senior data scientist, principal data scientist

    • Quantitative Finance - Quantitative analyst, quant researcher, quantitative trader

    • Software Engineering - Software engineer, algorithm developer, computational engineer

    • Financial Modeling - Financial modeller, risk modeler, derivatives modeler

    • Research - Mathematical researcher, computational researcher, applied mathematician

    • Algorithm Development - Algorithm developer, optimization specialist, computational scientist

    • Risk Analysis - Risk analyst, quantitative risk manager, model validation

    • Computational Biology - Computational biologist, bioinformatics scientist, systems biologist

    • Consulting - Data analytics consultant, quantitative consultant, mathematical modeling consultant

    • Machine Learning - Machine learning engineer, ML scientist, AI algorithm developer

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