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Course overview

Maths plays a bigger role in society than simply banking and finance. It is widely used to help understand the origins of the universe. It is even being used to help find a cure for cancer.

At Nottingham, we teach and undertake research. You'll learn about different aspects of mathematics from pure and applied mathematicians, theoretical physicists and statisticians. These specialisms mean we offer an extensive choice of modules. Your options range from cryptography to quantum theory, or finance to fluid dynamics.

Our peer mentoring programme will support your step up to university maths. You'll be surrounded by like-minded students who are passionate about mathematics and the role it has in modern life.

Gain in-depth mathematical knowledge and problem-solving skills. Your ability to think analytically and to understand and interpret complex data will be attractive to future employers. Our graduates work in computing, financial services, engineering, education and healthcare.

Why choose this course?

  • Accredited by the Institute of Mathematics & its Applications
  • Help with first-year topics through the Peer-Assisted Study Support programme (PASS) run by like-minded maths students
  • Flexibility to transfer onto the MMath integrated masters degree during the first two years
  • Study abroad in countries such as Australia, Canada or the USA
  • Paid research internship opportunities
  • Optional work placement year available

Entry requirements

All candidates are considered on an individual basis and we accept a broad range of qualifications. The entrance requirements below apply to 2021 entry.

UK entry requirements
A level offer A*AA/AAA/A*AB
Required subjects

At least A in A level mathematics. Required grades depend on whether A/AS level further mathematics is offered.

IB score IB 36; 6 in maths at Higher Level

STEP/MAT/TMUA is not required but may be taken into consideration when offered.

A level General Studies, Critical Thinking and Citizenship Studies are not accepted.

English 4 (C) at GCSE (or equivalent) 

Alternative qualifications

In all cases we require applicants to have at least the equivalent of A level Mathematics, so we typically only accept alternative qualifications when combined with an appropriate grade in A level Mathematics.

Foundation progression options

If you don't meet our entry requirements there is the option to study the engineering and physical sciences foundation programme. If you satisfy the progression requirements, you can progress to any of our mathematics courses. 

Find out more at Engineering and Physical Sciences Foundation Certificate

Learning and assessment

How you will learn

Teaching methods

  • Computer labs
  • Lectures
  • Tutorials
  • Problem classes

How you will be assessed

You will be given a copy of our marking criteria which provides guidance on how your work is assessed. Your work will be marked in a timely manner and you will receive regular feedback. The pass mark for each module is 40%.

Your final degree classification will be based on marks gained for your second and subsequent years of study. Year two is worth 33% with year three worth 67%.

Assessment methods

  • Coursework
  • Group project
  • Poster presentation
  • Research project
  • Written exam

Contact time and study hours

The majority of modules are worth 10 or 20 credits.  You will study modules totalling 120 credits in each year. As a guide one credit equates to approximately 10 hours of work. During the first year, you will typically  spend approximately:

  • 12 hours a week in lectures
  • 4 hours a week in problem classes
  • 1 hour each week in tutorials with your personal tutor
  • 1 hour a week in computing workshops across the Autumn and Spring terms
  • 1 hour each fortnight in student-led academic mentoring Peer-Assisted Study Support (PASS)

You can attend optional drop-in sessions each week up to a maximum of three hours and the remaining time will be spent in independent study.

In later years, you are likely to spend approximately 12 hours per week in lectures subject to the modules chosen.

During term time in your first year you will meet with your personal tutor every week in groups of five to six students to run through core topics. Lectures in the first two years often include at least 200 students but class sizes are much more variable in the third year subject to module selection.

Core modules are typically delivered by a mixture of Professors, Associate Professors and Lecturers, supported by PhD students in problem classes and computer lab sessions.

Study abroad

You can apply to spend a period of time studying abroad (usually one semester) through the University-wide exchange programme.

Students who choose to study abroad are more likely to achieve a first-class degree and earn more on average than students who did not (Gone International:Rising Aspirations report 2016/17).

Benefits of studying abroad

  • Explore a new culture
  • A reduction in tuition fee of up to 30% for the year in which you study abroad
  • Improve your communication skills, confidence and independence

Countries you could go to:

  • Australia
  • Canada
  • China (teaching is in English)
  • France
  • Germany
  • Italy
  • New Zealand
  • Singapore (teaching is in English)
  • Spain
  • USA

To study abroad you need to achieve a 60% average mark at the time of application. A good academic reference and personal statement  should be provided as part of the application process.

The marks gained overseas will count back to your Nottingham degree programme.

Year in industry

A placement year can improve your employability.

A report by High Fliers in 2019 found that over a third of recruiters who took part in their research said that graduates who have no previous work experience at all are unlikely to be successful during the selection process for their graduate programmes.

You can apply to do a placement year between years two and three. This would add an extra year to your degree. You'll pay a reduced tuition fee for this year.

Although it is your responsibility to find a placement, you'll have help from the school and the Careers and Employability Service. It could be in the UK or abroad. While on placement, you'll be supported by a Placement Tutor.

If you are interested in spending a year in industry as part of your named degree,  find out more at  BSc Mathematics with a Year in Industry.

Modules

Core modules

Analytical and Computational Foundations

This module introduces students to a broad range of core mathematical concepts and techniques. It has three components.

  • Mathematical reasoning (the language of mathematics, the need for rigour, and methods of proof).
  • The computer package MATLAB and its applications.
  • Elementary analysis.
Applied Mathematics

You will receive an introduction to classical mechanics and modelling in applied mathematics. This will provide you with a foundation in applied mathematics and you will begin to apply your knowledge to real world problems.

Calculus

You will begin by practising the basic concepts and methods of calculus including limits, functions, and continuity. In the second semester you will move onto more advanced usage of calculus. Topics will be based around the calculus of functions of several variables and include partial derivatives, chain rules, the vector operator grad, Lagrange multipliers and multiple integrals.

Foundations of Pure Mathematics

This module provides a foundation for all further pure mathematics studies on your course. You will learn that pure mathematics is a language based on the notion of sets, functions and relations, and how to read and write this language. There will also be discussions with examples on the application and use of pure mathematics.

Linear Mathematics

This module introduces you to the methods and practices of linear mathematics that you will need in subsequent modules on your course, such as complex numbers, vector algebra and matrix algebra. You will then expand your knowledge to include vector spaces, linear transformations and inner product spaces.

Mathematical Structures

This module provides an introduction to axiomatic systems in mathematics.It will cover the basic concepts of some key mathematical structures from algebra (groups, rings and fields) together with the basic properties of permutations, integers and polynomials.

Probability

This module provides an introduction to probability by developing a framework for the logic of uncertainty. Random variables and the topics surrounding them will also be introduced.

Statistics

This module offers you the chance to learn about a range of statistical ideas and skills, along with concepts and techniques for modelling and practical data analysis. You will learn to write reports based on these topics which will help you in further studies.

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules may change or be updated over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for the latest information on available modules.

Choosing from a range of optional modules, you will continue to study two of the three main mathematical subject areas. You will also have the option to choose some modules (up to 20 credits) from outside of mathematics.

You must take a minimum of 100 and a maximum of 120 credits from the below.

Optional modules

Algebra and Number Theory

This course will develop in more detail the fundamental concepts in algebra such as groups and rings and will provide an introduction to elementary number theory.

We will consider how general algebraic concepts can be applied in concrete situations in number theory and after a review of primes, integer factorization and module arithmetic, the focus will be on classical problems. This includes Fermat’s Little Theorem and its application to primality testing, methods of factorization, primitive roots, discrete logarithms, some classical Diophantine equations (linear and polynomial), Fibonacci numbers, and continued fractions.

Complex Functions

In this module you will learn about the theory and applications of functions of a complex variable using a method and applications approach. You will develop an understanding of the theory of complex functions and evaluate certain real integrals using your new skills.

Differential Equations and Fourier Analysis

This course is an introduction to Fourier series and integral transforms and to methods of solving some standard ordinary and partial differential equations which occur in applied mathematics and mathematical physics.

The course describes the solution of ordinary differential equations using series and introduces Fourier series and Fourier and Laplace transforms, with applications to differential equations and signal analysis. Standard examples of partial differential equations are introduced and solution using separation of variables is discussed.

Introduction to Mathematical Physics
This course develops Newtonian mechanics into the more powerful formulations due to Lagrange and Hamilton and introduces the basic structure of quantum mechanics. The course provides the foundation for a wide range of more advanced courses in mathematical physics.
Introduction to Scientific Computation

This module introduces basic techniques in numerical methods and numerical analysis which can be used to generate approximate solutions to problems that may not be amenable to analysis. Specific topics include:

  • Implementing algorithms in Matlab
  • Discussion of errors (including rounding errors)
  • Iterative methods for nonlinear equations (simple iteration, bisection, Newton, convergence)
  • Gaussian elimination, matrix factorisation, and pivoting
  • Iterative methods for linear systems, matrix norms, convergence, Jacobi, Gauss-Siedel
  • Interpolation (Lagrange polynomials, orthogonal polynomials, splines)
  • Numerical differentiation & integration (Difference formulae, Richardson extrapolation, simple and composite quadrature rules)
  • Introduction to numerical ODEs (Euler and Runge-Kutta methods, consistency, stability) 
Mathematical Analysis

In this module you will build on the foundation of knowledge gained from your core year one modules in Analytical and Computational Foundations and Calculus. You will learn to follow a rigorous approach needed to produce concrete proof of your workings.

Modelling with Differential Equations

This course aims to provide students with tools which enable them to develop and analyse linear and nonlinear mathematical models based on ordinary and partial differential equations. Furthermore, it aims to introduce students to the fundamental mathematical concepts required to model the flow of liquids and gases and to apply the resulting theory to model physical situations. 

Probability Models and Methods

This module will give you an introduction to the theory of probability and random variables, with particular attention paid to continuous random variables. Fundamental concepts relating to probability will be discussed in detail, including well-known limit theorems and the multivariate normal distribution. You will then progress onto complex topics such as transition matrices, one-dimensional random walks and absorption probabilities.

Statistical Models and Methods

The first part of this module provides an introduction to statistical concepts and methods and the second part introduces a wide range of techniques used in a variety of quantitative subjects. The key concepts of inference including estimation and hypothesis testing will be described as well as practical data analysis and assessment of model adequacy.

Vector Calculus

This course aims to give students a sound grounding in the application of both differential and integral calculus to vectors, and to apply vector calculus methods and separation of variables to the solution of partial differential equations. The module is an important pre-requisite for a wide range of other courses in Applied Mathematics.

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules may change or be updated over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for the latest information on available modules.

You must take a minimum of 100 and a maximum of 120 credits from the below.You will also have the option to choose some modules from outside mathematics if you wish.

Optional modules

Advanced Quantum Theory

In this module you will apply the general theory you learnt in Introduction to Mathematical Physics to more general problems. New topics will be introduced such as the quantum theory of the hydrogen atom and aspects of angular momentum such as spin.

Applied Statistical Modelling

In this module you will build on your theoretical knowledge of statistical inference by a practical implementation of the generalised linear model. You will move on to enhance your understanding of statistical methodology including the analysis of discrete and survival data. You will also be trained in the use of a high-level statistical computer program.

Classical and Quantum Dynamics

The course introduces and explores methods, concepts and paradigm models for classical and quantum mechanical dynamics exploring how classical concepts enter quantum mechanics, and how they can be used to find approximate semi-classical solutions.

In classical dynamics we discuss full integrability and basic notions of chaos in the framework of Hamiltonian systems, together with advanced methods like canonical transformations, generating functions and Hamiltonian-Jacobi theory. In quantum mechanics we recall Schrödinger's equation and introduce the semi-classical approximation. We derive the Bohr-Sommerfeld quantization conditions based on a WKB-approch to the eigenstates. We will discuss some quantum signatures of classical chaos and relate them to predictions of random-matrix theory. We will also introduce Gaussian states and coherent states and discuss their semi-classical dynamics and how it is related to the corresponding classical dynamics. An elementary introduction to complete descriptions of quantum mechanics in terms of functions on the classical phase space will be given.

Coding and Cryptography

This course provides an introduction to coding theory in particular to error-correcting codes and their uses and applications. It also provides an introduction to to cryptography, including classical mono- and polyalphabetic ciphers as well as modern public key cryptography and digital signatures, their uses and applications.

Data Analysis and Modelling

This module involves the application of probability and statistics to a variety of practical, open-ended problems, typical of those that statisticians encounter in industry and commerce. Specific projects are tackled through workshops and student-led group activities.

The real-life nature of the problems requires students to develop skills in model development and refinement, report writing and teamwork. Students will have an opportunity to apply a variety of statistical methods and knowledge learned in previous modules.

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Differential Equations

This course introduces various analytical methods for the solution of ordinary and partial differential equations, focussing on asymptotic techniques and dynamical systems theory. Students taking this course will build on their understanding of differential equations covered in Modelling with Differential Equations.

Elliptic Curves

The course will start with several topics from the perspective of what can be explicitly calculated with an emphasis on applications to geometry and number theory.

Topics include:

  • basic notions of projective geometry
  • plane algebraic curves including elliptic curves
  • addition of points on elliptic curves 
  • results on the group of rational points on an elliptic curve
  • properties of elliptic curves and their applications.
Electromagnetism

The course provides an introduction to electromagnetism and the electrodynamics of charged particles. The aims of this course are:

  • to develop an appropriate mathematical model of electromagnetic phenomena that is informed by observations
  • to understand electromagnetic configurations of practical importance and to relate predictions made to everyday phenomena
  • to illustrate the use of solutions of certain canonical partial differential equations for determining electrostatic fields and electromagnetic waves in vacuum and in matter
  • to illustrate the interplay between experimental input and the development of a mathematical model, and the use of various mathematical techniques for solving relevant problems.
Fluid Dynamics
This course aims to extend previous knowledge of fluid flow by introducing the concept of viscosity and studying the fundamental governing equations for the motion of liquids and gases. Methods for solution of these equations are introduced, including exact solutions and approximate solutions valid for thin layers. A further aim is to apply the theory to model fluid dynamical problems of physical relevance.
Further Number Theory

Number theory concerns the solution of polynomial equations in whole numbers, or fractions. For example, the cubic equation x3 + y3 = z3 with x, y, z non-zero has infinitely many real solutions yet not a single solution in whole numbers.

We shall establish the basic properties of the Riemann zeta-function to find out how evenly these primes are distributed in nature. This course will present several methods to solve Diophantine equations including analytical methods using zeta-functions and Dirichlet series, theta functions and their applications to arithmetic problems, and an introduction to more general modular forms.

Game Theory
Game theory contains many branches of mathematics (and computing); the emphasis here is primarily algorithmic. The module starts with an investigation into normal-form games, including strategic dominance, Nash equilibria, and the Prisoner’s Dilemma. We look at tree-searching, including alpha-beta pruning, the ‘killer’ heuristic and its relatives. It then turns to mathematical theory of games; exploring the connection between numbers and games, including Sprague-Grundy theory and the reduction of impartial games to Nim.
Graph Theory

A graph (in the sense used in Graph Theory) consists of vertices and edges, each edge joining two vertices. Graph Theory has become increasingly important recently through its connections with computer science and its ability to model many practical situations. 

Topics covered in the course include:

  • paths and cycles
  • the resolution of Euler’s Königsberg Bridge Problem
  • Hamiltonian cycles
  • trees and forests
  • labelled trees,
  • the Prüfer correspondence
  • planar graphs
  • Demoucron et al. algorithm
  • Kruskal's algorithm
  • the Travelling Salesman's problem
  • the statement of the four-colour map theorem
  • colourings of vertices
  • chromatic polynomial
  • colourings of edges.
Group Theory

This course builds on the basic ideas of group theory. It covers a number of key results such as the simplicity of the alternating groups, the Sylow theorems (of fundamental importance in abstract group theory), and the classification of finitely generated abelian groups (required in algebraic number theory, combinatorial group theory and elsewhere). Other topics to be covered are group actions, used to prove the Sylow theorems, and series for groups, including the notion of solvable groups that will be used in Galois theory.

Linear Analysis

This module gives an introduction into some basic ideas of functional analysis with an emphasis on Hilbert spaces and operators on them.

Many concepts from linear algebra in finite dimensional vector spaces (e.g. writing a vector in terms of a basis, eigenvalues of a linear map, diagonalisation etc.) have generalisations in the setting of infinite dimensional spaces making this theory a powerful tool with many applications in pure and applied mathematics

Mathematical Finance

In this module the concepts of discrete time Markov chains are explored and used to provide an introduction to probabilistic and stochastic modelling for investment strategies, and for the pricing of financial derivatives in risky markets. You will gain well-rounded knowledge of contemporary issues which are of importance in research and applications.

Mathematical Medicine and Biology
Mathematics can be usefully applied to a wide range of applications in medicine and biology. Without assuming any prior biological knowledge, this course describes how mathematics helps us understand topics such as population dynamics, biological oscillations, pattern formation and nonlinear growth phenomena. There is considerable emphasis on model building and development.
Mathematics Project

This module consists of a self-directed investigation of a project selected from a list of projects or, subject to prior approval of the School, from elsewhere.

Project modules are carried out in the Autumn and Spring semesters.

The project will be supervised by a member of staff and will be based on a substantial mathematical problem, an application of mathematics or investigation of an area of mathematics not previously studied by the student. The course includes training in the use of IT resources, the word-processing of mathematics and report writing.

Metric and Topological Spaces

Metric space generalises the concept of distance familiar from Euclidean space. It provides a notion of continuity for functions between quite general spaces.

The module covers metric spaces, topological spaces, compactness, separation properties like Hausdorffness and normality, Urysohn’s lemma, quotient and product topologies, and connectedness. Finally, Borel sets and measurable spaces are introduced.

Multivariate Analysis

This module is concerned with the analysis of multivariate data, in which the response is a vector of random variables rather than a single random variable. A theme running through the module is that of dimension reduction. Key topics to be covered include: principal components analysis, whose purpose is to identify the main modes of variation in a multivariate dataset; modelling and inference for multivariate data, including multivariate regression data, based on the multivariate normal distribution; classification of observation vectors into sub-populations using a training sample; canonical correlation analysis, whose purpose is to identify dependencies between two or more sets of random variables. Further topics to be covered include factor analysis, methods of clustering and multidimensional scaling.

Optimisation

In this module a variety of techniques and areas of mathematical optimisation will be covered including Lagrangian methods for optimisation, simplex algorithm linear programming and dynamic programming. You’ll develop techniques for application which can be used outside the mathematical arena. 

Relativity

In this module you’ll have an introduction to Einstein’s theory of general and special relativity. The relativistic laws of mechanics will be described within a unified framework of space and time. You’ll learn how to compare other theories against this work and you’ll be able to explain new phenomena which occur in relativity.

Rings and Modules

Commutative rings and modules over them are the fundamental objects of what is often referred to as commutative algebra. Already encountered key examples of commutative rings are polynomials in one variable over a field and number rings such as the usual integers or the Gaussian integers.

There are many close parallels between these two types of rings, for example the similarities between the prime factorization of integers and the factorization of polynomials into irreducibles. In this module, these ideas are extended and generalized to cover polynomials in several variables and power series, and algebraic numbers.

Scientific Computation and Numerical Analysis

You will learn how to use numerical techniques for determining the approximate solution of ordinary and partial differential equations where a solution cannot be found through analytical methods alone. You will also cover topics in numerical linear algebra, discovering how to solve very large systems of equations and find their eigenvalues and eigenvectors using a computer.

Statistical Inference

This course is concerned with the two main theories of statistical inference, namely classical (frequentist) inference and Bayesian inference. 

Topics such as sufficiency, estimating equations, likelihood ratio tests and best-unbiased estimators are explored in detail. There is special emphasis on the exponential family of distributions, which includes many standard distributions such as the normal, Poisson, binomial and gamma.

In Bayesian inference, there are three basic ingredients: a prior distribution, a likelihood and a posterior distribution, which are linked by Bayes' theorem. Inference is based on the posterior distribution, and topics including conjugacy, vague prior knowledge, marginal and predictive inference, decision theory, normal inverse gamma inference, and categorical data are pursued.

Common concepts, such as likelihood and sufficiency, are used to link and contrast the two approaches to inference. You will gain experience of the theory and concepts underlying much contemporary research in statistical inference and methodology.

Stochastic Models

In this module you will develop your knowledge of discrete-time Markov chains by applying them to a range of stochastic models. You will be introduced to Poisson and birth-and-death processes and then you will move onto more extensive studies of epidemic models and queuing models with introductions to component and system reliability.

Vocational Mathematics

This module involves the application of mathematics to a variety of practical, open-ended problems, typical of those that mathematicians encounter in industry and commerce. Specific projects are tackled through workshops and student-led group activities. The real-life nature of the problems requires students to develop skills in model development and refinement, report writing and teamwork.

The above is a sample of the typical modules we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Modules may change or be updated over the duration of the course due to a number of reasons such as curriculum developments or staffing changes. Please refer to the module catalogue for the latest information on available modules.
  • Become a PASS leader in your second or third year. Teaching first-year students reinforces your own mathematical knowledge. It develops communication, organisational and time management skills which can help to enhance your CV when you start applying for jobs
  • The Nottingham Internship Scheme provides a range of  paid work experience opportunities and internships throughout the year
  • The Nottingham Advantage Award is our free scheme to boost your employability. There are over 200 extracurricular activities to choose from
  • Nottingham MathSoc offers students a chance to enjoy various activities with like minded individuals also studying mathematics. Examples of events are balls, river cruises, sport and other social activities.

Fees and funding

UK students

£9,250
Per year

International students

To be confirmed in 2020*
Keep checking back for more information
*For full details including fees for part-time students and reduced fees during your time studying abroad or on placement (where applicable), see our fees page.

If you are a student from the EU, EEA or Switzerland starting your course in the 2021/22 academic year, you will pay international tuition fees.

This does not apply to Irish students, who will be charged tuition fees at the same rate as UK students. UK nationals living in the EU, EEA and Switzerland will also continue to be eligible for ‘home’ fee status at UK universities until 31 December 2027.

For further guidance, check our Brexit information for future students.

Additional costs

As a student on this course, you should factor some additional costs into your budget, alongside your tuition fees and living expenses.

You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies.

Due to our commitment to sustainability, we don’t print lecture notes but these are available digitally. You will be given £5 worth of printer credits a year. You are welcome to buy more credits if you need them. It costs 4p to print one black and white page.

If you study abroad, you need to consider the travel and living costs associated with your country of choice. This may include visa costs and medical insurance. 

Personal laptops are not compulsory as we have computer labs that are open 24 hours a day but you may want to consider one if you wish to work at home.  

Scholarships and bursaries

We offer an international orientation scholarship of £2,000 to the best international (full-time, non EU) applicants on this course.

It will be paid at most once for each year of study. If you repeat a year for any reason, the scholarship will not be paid for that repeated year. The scholarship is awarded in subsequent years to students who perform well academically (at the level of a 2:1 Hons degree or better at the first attempt). 

The scholarship will be paid in December each year provided you have:

  • completed your registration
  • been recorded as a student on a relevant course in the 1 December census
  • paid the first instalment of your fee

Home students*

Over one third of our UK students receive our means-tested core bursary, worth up to £1,000 a year. Full details can be found on our financial support pages.

* A 'home' student is one who meets certain UK residence criteria. These are the same criteria as apply to eligibility for home funding from Student Finance.

International/EU students

We offer a range of Undergraduate Excellence Awards for high-achieving international and EU scholars from countries around the world, who can put their Nottingham degree to great use in their careers. This includes our European Union Undergraduate Excellence Award for EU students and our UK International Undergraduate Excellence Award for international students based in the UK.

These scholarships cover a contribution towards tuition fees in the first year of your course. Candidates must apply for an undergraduate degree course and receive an offer before applying for scholarships. Check the links above for full scholarship details, application deadlines and how to apply.

Careers

Mathematics is a broad and versatile subject leading to many possible careers. Our graduates are helping to shape the future in many sectors including banking and finance, business consulting and management. Other employment sectors include education, local and central government and some graduates pursue a career in mathematical research.

They have jobs such as:

  • Actuary
  • Graduate analyst
  • IT consultant
  • Software engineer
  • Maths tutor

Our graduates have gone to work for companies such as:

  • MBNA
  • Capital One
  • HSBC
  • Deloitte
  • PwC
  • KPMG
  • British Airways
  • BAE Sytems
  • Applied International
  • NHS

Average starting salary and career progression

83.8% of undergraduates from the School of Mathematical Sciences secured graduate level employment or further study within 15 months of graduation. The average annual salary for these graduates was £26,985.*

* HESA Graduate Outcomes 2020. The Graduate Outcomes % is derived using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.

Studying for a degree at the University of Nottingham will provide you with the type of skills and experiences that will prove invaluable in any career, whichever direction you decide to take.

Throughout your time with us, our Careers and Employability Service can work with you to improve your employability skills even further; assisting with job or course applications, searching for appropriate work experience placements and hosting events to bring you closer to a wide range of prospective employers.

Have a look at our careers page for an overview of all the employability support and opportunities that we provide to current students.

The University of Nottingham is consistently named as one of the most targeted universities by Britain’s leading graduate employers (Ranked in the top ten in The Graduate Market in 2013-2020, High Fliers Research).

Institute of Mathematics and its Applications

This programme will meet the educational requirements of the Chartered Mathematician designation, awarded by the Institute of Mathematics and its Applications, when it is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency (QAA) for taught masters degrees.

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" The main aspect of my course which I have enjoyed the most is the fact that it offers a wide range of optional modules in your second and third years. I enjoyed having a variety of topics such as pure based modules, applied mathematics and statistics and probability. "
Lucy Edwards, BSc Mathematics

Related courses

The University has been awarded Gold for outstanding teaching and learning

Teaching Excellence Framework (TEF) 2017-18

Disclaimer

This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.