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Start Dates
Degree type

MMath

Course length

4 years full-time

Location

Durham City

UCAS code

G114

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Typical offers

Typical offers
A Level A*A*A/A*AA
BTEC D*D*D/D*DD
International Baccalaureate 38

Course details

This challenging degree takes your study of Mathematics and Statistics to Master’s level. It is the ideal choice if you are considering postgraduate study or a career that requires high-level numeracy skills or research.

The MMath combines a strong mathematical grounding with the latest developments in statistics and machine learning to provide the foundation you’ll need to step into a data-driven workplace. The first two years follow a similar structure to the BSc. The wider range of modules introduced in Years 3 and 4 explore more sophisticated mathematical and statistical techniques in greater depth.

The course is based in a brand-new facility, purpose-built to meet the learning, teaching and study needs of students from the Department. You will be taught by a team of mathematicians and statisticians with a wealth of experience in industry and research. The Department is home to a number of research groups with specialisms in both pure and applied mathematics. With many members of the teaching team actively involved in research there are plenty of opportunities to link learning to the latest research in distinctive and creative ways.

The first year begins with a broad-based introduction to pure and applied mathematics, statistics and probability and provides a sound foundation for in-depth study in subsequent years. As you move into the second and third year the focus on statistics increases.

During the final year you complete a double-module project. This can be the individual project in which you tackle a theoretical area or an applied problem in depth. Alternatively, the internship project is a statistics and machine learning piece of work based on a third-party problem. Both projects can be carried out in collaboration with external organisations to add valuable real-world context to your degree.

Course structure

Year 1

Core modules:

Analysis aims to provide an understanding of real and complex number systems, and to develop rigorously the calculus of functions of a single variable from basic principles.

Calculus builds on ideas of differentiation and integration in A level mathematics, beginning with functions of a single variable and moving on to functions of several variables. Topics include methods of solving ordinary and partial differential equations, and an introduction to Fourier Series and Fourier transforms.

Linear Algebra presents mathematical ideas, techniques in linear algebra and develops geometric intuition and familiarity with vector methods in preparation for more demanding material later in the course.

Dynamics develops an understanding of elementary classical Newtonian dynamics as well as an ability to formulate and solve basic problems in dynamics.

Probability introduces mathematics ideas on probability in preparation for more specialised material later in the course. The module presents a mathematical subject of key importance to the real-world (applied) that is based on rigorous mathematical foundations (pure).

Programming is taught via lectures and practical sessions that introduce basic principles and competence in computer programming. You will also study control structures; floating point arithmetic; and lists, strings and introduction to objects.

Statistics introduces frequentist and Bayesian statistics and demonstrates the relevance of these principles and procedures to real problems. This module lays the foundations for all subsequent study of statistics.

Year 2

Core modules:

Analysis in Many Variables provides an understanding of calculus in more than one dimension, together with an understanding of, and facility with, the methods of vector calculus. It also explores the application of these ideas to a range of forms of integration and to solutions of a range of classical partial differential equations.

Statistical Inference introduces the main concepts underlying statistical inference and methods. This module develops the foundations underlying classical statistical techniques, and the basis for the Bayesian approach to statistics. You will also investigate and compare frequentist and Bayesian approaches.

Data Science and Statistical Computing equips you with the skills to import, explore, manipulate, model and visualise real data sets using the statistical programming language R. The module introduces the concepts and mathematics behind sampling. It also covers data protection and governance issues when working with data.

Statistical Modelling provides a working knowledge of the theory, computation and practice of the linear model. You will cover areas including analysis of variance, model selection, diagnostics and transformation methods.

In recent years, optional modules have included:

  • Algebra
  • Complex Analysis
  • Mathematical Physics
  • Numerical Analysis
  • Elementary Number Theory
  • Geometric Topology
  • Markov Chains
  • Mathematical Modelling
  • Probability
  • Special Relativity and Electromagnetism.

Year 3

In recent years, optional modules have included:

  • Advanced Statistical Modelling
  • Bayesian Computation and Modelling
  • Decision Theory
  • Machine Learning and Neural Networks
  • Mathematical Finance
  • Stochastic Processes.

Year 4

Core modules:

In the final year Project you will investigate a statistical topic of interest or perform an in-depth analysis of a data set using the tools acquired earlier in the course. You then produce a written report and give a short presentation. Subject to availability, you may have the opportunity to perform this project in collaboration with an external organisation. The project develops your research and communication skills which are important for future employment or postgraduate studies.

Or

The Internship Project gives you the opportunity to conduct a substantial piece of independent statistics and machine learning work in a real-world context working with a third party, and to write up and present this work. This will further your analytical, collaborative and transferable skills, and your knowledge of the practice of statistics and machine learning, as well as advance your abilities in oral or written communication.

In recent years, optional modules have included:

  • Spatio-Temporal Statistics
  • Deep Learning and Artificial Intelligence
  • Discrete and Continuous Probability
  • High-Dimensional Data Analysis
  • Non-Parametric Statistics
  • Object-Oriented Statistics
  • Robust Bayesian Analysis
  • Topics in Probability
  • Uncertainty Quantification.

Additional pathways

You can further tailor your course by applying to be transferred onto either the ‘with Year Abroad’ or ‘with Placement’ pathway during the second year. Places on these pathways are in high demand, and if you are chosen your course will extend from four years to five.

Placement

You may be able to take a work placement. Find out more.

Learning

Methods of teaching and learning include lectures, tutorials, problem classes, homework problems, written and oral presentations and individual projects. You will also take part in computer practicals, in which you learn how to implement computational methods and how to analyse real data.

For most modules you will attend two lectures a week. Mathematical questions are set in lectures and may form the topic of discussion in tutorials or problem classes. The best way to learn maths is to work through problems, so in addition to independent study we recommend collaborative working with other students.

The final-year project is organised around fortnightly small-group meetings with lecturers. You are free to choose the remaining modules from a range of subjects including statistics, machine learning, and probability, plus a teaching module in which you study how pupils learn in school.

Assessment

We use a combination of methods to assess the different modules, these include written examinations, computer-based examinations, project reports and presentations of project work. In your final year you also complete an in-depth project which is worth one-third of your final-year marks.

Entry requirements

A level offer – A*A*A-A*AA

Suitable performance in the University Admission Tests TMUA or MAT or 2 in any STEP will lead to the lower A*AA offer (A*A in Mathematics and Further Mathematics, either way round plus A in any other A level or equivalent).

BTEC Level 3 National Extended Diploma / OCR Cambridge Technical Extended Diploma – D*D*D – D*DD and A level requirements as above.

IB Diploma score – 38 with 776 including a 7 in Mathematics (Analysis & Approaches) or 766 in higher level subjects, including a 7 in Mathematics (Analysis & Approaches).

In addition to satisfying the University’s general entry requirements, please note that:

  • We strongly encourage applicants to sit the University’s Admissions Test (*) if it is available to them, as we give a high weighting in our selection process to evidence of ability in Mathematics.
  • We welcome applications from those with other qualifications equivalent to our standard entry requirements and from mature students with non-standard qualifications or who may have had a break in their study. Please contact our Admissions Selectors.
  • If you are an international student who does not meet the requirements for direct entry to this degree you may be eligible to take an International Foundation Year pathway programme at the Durham University International Study Centre
  • We are pleased to consider applications for deferred entry, although we advise you to make sure that you take steps to maintain your level of mathematical expertise.

(*) The University uses a national Admission Test in Mathematics (TMUA), in conjunction with the Cambridge Assessment Admissions Testing (CAAT). Test results will be sent by the CAAT directly to students at the end of November, and all information concerning the Test (including whether it was taken at all) will be provided to us by the applicants on an entirely voluntarily basis: suitable performance will entitle the applicant to the reduced A*AA offer. Taking part in the TMUA can therefore only increase the chances of receiving an offer. More information can be found on the Mathematics Department website, on the CAAT website and in most schools nationwide. (Schools that currently administer STEP and MAT will be automatically registered).

Alternative qualifications

International students who do not meet direct entry requirements for this degree might have the option to complete an International Foundation Year.

English language requirements

Country specific information

Fees and funding

Full Time Fees

Tuition fees
Home students £9,250 per year
EU students £27,000 per year
Island students £9,250 per year
International students £27,000 per year

The tuition fees shown for home students are for one complete academic year of full time study and are set according to the academic year of entry. Fees for subsequent years of your course may rise in line with an inflationary uplift as determined by the government.

The tuition fees shown for overseas and EU students are for one complete academic year of full time study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).

Please also check costs for colleges and accommodation.

Scholarships and Bursaries

We are committed to supporting the best students irrespective of financial circumstances and are delighted to offer a range of funding opportunities. 

Find out more about Scholarships and Bursaries

Career opportunities

Mathematical Sciences

As well as developing you academically, a Durham University degree will equip you with a range of practical skills including critical thinking, an analytical approach and ability to reason with information, alongside experience in building relationships and leading teams.

A significant number of our students progress to higher level study following their degree. Some remain within their academic field of interest and pursue higher level research, notably at Durham but also other prestigious institutions. Others take a different route and pursue postgraduate programmes or employment in areas from statistics and financial management to conservation and teaching.

Some of the high-profile employers our graduates have gone on to work for include Royal London, Deloitte, CERN, Morgan Stanley and Ocado.

Of those students who graduated in 2019:

  • 94% are in paid employment or further study 15 months after graduation across all our programmes

Of those in employment:

  • 89% are in high skilled employment
  • With an average salary of £31,000.

(Source: HESA Graduate Outcomes Survey. The survey asks leavers from higher education what they are doing 15 months after graduation. Further information about the Graduate Outcomes survey can be found here www.graduateoutcomes.ac.uk)

Department information

Mathematical Sciences

Mathematical Sciences offers a high-quality education that is taught by subject specialists, informed by the latest research and delivered in a stimulating academic environment. Using distinctive and creative methods, we do all we can to incorporate relevant aspects of the Department’s world-leading research into the undergraduate curriculum.

We offer a range of degrees which give you a choice from a wide spectrum of pure mathematics, applied mathematics (including mathematical physics) and statistics.

The overall aim is to develop you as a member of the community of professional mathematicians. Degrees combine theoretical learning with practicals and mini projects, enabling you to develop your capacity for critical thinking, problem-solving and independent learning, which will equip you with the skills to meet a variety of challenges in the workplace. We seek to develop both the generic and subject-specific skills you need to pursue a range of careers, and to further develop your skills we offer the opportunity to spend a year studying overseas or working in industry.

For more information visit our department pages.

Rankings

  • 11th in The Complete University Guide 2024

Staff

For a current list of staff, please see the Mathematical Sciences department pages.

Research Excellence Framework

  • 96% of our research outputs are world-leading or internationally excellent (REF 2021).

Facilities

The Department lies in the heart of the University on the Upper Mountjoy campus near to the University library and the science and engineering departments. We share our purpose-built £40 million new building with Computer Sciences given the natural synergy between the subjects. It is also home to several supercomputers, keeping our education at the forefront of innovation.

The building provides cutting-edge learning, teaching and study areas, with plenty of space for group work to deepen the Durham experience and enhance the staff-student relationship.

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Use the UCAS code below when applying:

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G114

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