Mathematics with Computing BSc (Hons)

3 Years On Campus Bachelors Program

Queen Mary University of London

Program Overview

The Mathematics with Computing BSc (Hons) at Queen Mary University of London blends rigorous mathematical training with practical computing skills. The programme suits students who enjoy analytical thinking and want to apply mathematics to real-world computational and data-driven challenges.

Curriculum structure:

Year 1
The first year builds a strong foundation in core mathematical principles and programming. Students study modules such as Introduction to Analysis with Calculus, Numbers, Sets and Functions, Vectors and Matrices, Probability & Statistics, Object-Oriented Programming, and Programming in Python I. These modules establish essential problem-solving, logical reasoning and coding skills.

Year 2
The second year progresses into more advanced mathematical methods and computing concepts. Students take core modules including Differential Equations, Linear Algebra I, Probability & Statistics II, Data Structures and Algorithms, Theory of Computing, and Professional Skills for Mathematicians. Optional choices such as Complex Variables, Linear Programming and Games, and Statistical Modelling I allow students to shape their academic direction.

Year 3
In the final year, students undertake the Mathematics with Computing Project, where they independently explore a chosen mathematical-computational topic. Core study includes Numerical Computing with C and C++, providing strong numerical and programming capability. A wide range of optional modules — including Computer Graphics, Algorithmic Graph Theory, Deep Learning, Introduction to Machine Learning, Numerical Analysis, and Random Processes — enables students to specialize in areas aligned with data science, advanced mathematics or theoretical computing.

Focus areas:
Mathematics, programming, algorithms, data structures, numerical computing, probability and statistics, machine learning, data-driven computation, computational mathematics.

Learning outcomes:
Students graduate with strong analytical and numerical abilities, proficiency in Python and C/C++, and the capacity to model, analyse and solve complex computational problems. They develop the technical and mathematical grounding needed for careers in data science, finance, technology and quantitative fields.

Professional alignment (accreditation):
The programme aligns with professional standards in mathematics, computing and data-intensive industries, preparing students for both technical roles and further academic study.

Reputation (employability rankings):
Queen Mary University of London is highly regarded for mathematics and computing, and its graduates are recruited by leading employers across finance, consulting, data analytics and technology. Many alumni secure roles with major firms such as global banks, consulting companies and technology organisations.

Experiential Learning (Research, Projects, Internships etc.)

The Mathematics with Computing degree at Queen Mary equips students with a powerful combination of theoretical mathematics and practical computing skills, preparing them for real-world challenges. From the beginning, students engage in programming (Python, C/C++), computational mathematics, and algorithmic problem solving. Learning takes place in well-equipped labs and collaborative spaces, allowing students to practice coding, numerical computing, and data modelling, often working in small groups or on projects.

Experiential Learning

Students gain hands-on experience and develop practical skills through a variety of facilities and activities:

Dedicated computing labs and teaching spaces in the School of Mathematical Sciences, featuring modern teaching rooms, private and group study areas, and social hubs.
Use of real programming languages and tools, including Python for first-year modules and C/C++ for numerical computing in later years.
Completion of a substantial third-year project combining mathematics and computing, which can be done individually or in small groups.
Option to take a professional placement year to gain paid work experience in industry.
Option to spend a year abroad at a partner university for global exposure and practical experience in an international context.
Flexible curriculum with electives such as machine learning, deep learning, computer graphics, coding theory, complex networks, numerical analysis, and number theory.
Strong employability support, including guidance from a dedicated careers consultant and opportunities to gain practical certifications.

Programme Structure

Year 1: Core mathematics (calculus, vectors and matrices, sets and functions), probability and statistics, and introductory programming in Python.
Year 2: Advanced mathematics (linear algebra, differential equations, probability and statistics II), computing fundamentals (data structures and algorithms, theory of computing), and professional skills for mathematicians.
Year 3 (or 4, with placement/year abroad): Major project combining mathematics and computing, numerical computing with C/C++, and electives to allow specialization.

The degree is available as a standard 3-year BSc, a 4-year BSc with a professional placement, or a 4-year BSc with a year abroad.

Facilities

Students benefit from dedicated computing labs, collaborative study spaces, modern teaching rooms, project support, and access to career guidance and certifications to enhance employability.

Progression & Future Opportunities

Graduates of the Mathematics with Computing BSc (Hons) at Queen Mary University of London (QMUL) typically move into roles such as data analyst or data scientist, quantitative/financial analyst, software or systems engineer, or insights/business analyst — often in finance, tech, consulting, or analytics-driven industries. Their strong blend of mathematical reasoning and computing skills also makes them attractive for roles in risk analysis, statistical modelling, and algorithm development.

Why This Degree Opens Doors:

University‑supported employability services: The QMUL School of Mathematical Sciences offers dedicated careers support, including internships coordination, CV and application coaching, interview preparation, and networking events.
Strong employment record & starting salary: Approximately 90% of graduates are in work or further study within six months of graduating. The typical starting salary is around £30,336, with some reports as high as £32,000 within 15 months.
Access to industry-leading employers: Recent graduates have secured positions at leading firms such as Accenture, Deloitte, KPMG, J.P. Morgan, Deutsche Bank, Bank of England, and many more across finance, consultancy, tech, and the public sector.
Accredited, high‑quality academic training with long‑term value: The programme combines rigorous mathematics (e.g., linear algebra, statistics, differential equations) with computing fundamentals (data structures, algorithms, theory of computing), which builds a strong foundation for both applied and theoretical work. These versatile analytical and computational skills remain relevant even as technology evolves.
Flexibility & global exposure: Students may opt for a version of the degree with a Year in Industry (professional placement) or a Year Abroad — enhancing real‑world experience or international exposure.
Diverse graduate outcomes: QMUL mathematics graduates enter varied careers — from software engineering and data science to finance, statistics, project management, consulting, and actuarial roles — enabling flexibility in career choice.

Further Academic Progression:
After completing the BSc, graduates may choose to deepen their expertise through a Master’s or research programme — for example in fields like data science, machine learning, quantitative finance, statistics, computational mathematics, or computer science. Alternatively, they could pursue professional qualifications (e.g., in actuarial science, finance, or data analytics) or even doctoral studies if they wish to engage in advanced research.