Clearing offers from 56 UCAS tariff points. Subject-specific requirements still apply. See the entry requirements section for details.
Mathematics helps us understand how the world works from predicting climate change and modelling financial markets to improving healthcare, cybersecurity, artificial intelligence, and engineering. Mathematics is also studied as a creative subject called pure mathematics where patterns, concepts, and ideas are explored in depth.
The MMath Mathematics degree at the University of Lincoln is designed for students who enjoy problem-solving, critical and logical thinking, and exploring how maths can be used to overcome real challenges. Whether you already know you want a career in data science, finance, technology, research, teaching, or industry, or you're still exploring your options, this course gives you the analytical and technical skills employers value across a huge range of sectors.
Unlike a standard three-year degree, the integrated four-year MMath programme allows you to study mathematics at a more advanced level and graduate with a master's qualification. You'll build strong foundations in pure and applied mathematics before progressing to specialist topics and independent research.
At Lincoln, you'll learn in a supportive environment with access to dedicated mathematics facilities, experienced academics, and a course designed to prepare you for graduate careers where advanced analytical skills are in demand.
Mathematics helps us understand how the world works from predicting climate change and modelling financial markets to improving healthcare, cybersecurity, artificial intelligence, and engineering. Mathematics is also studied as a creative subject called pure mathematics where patterns, concepts, and ideas are explored in depth.
The MMath Mathematics degree at the University of Lincoln is designed for students who enjoy problem-solving, critical and logical thinking, and exploring how maths can be used to overcome real challenges. Whether you already know you want a career in data science, finance, technology, research, teaching, or industry, or you're still exploring your options, this course gives you the analytical and technical skills employers value across a huge range of sectors.
Unlike a standard three-year degree, the integrated four-year MMath programme allows you to study mathematics at a more advanced level and graduate with a master's qualification. You'll build strong foundations in pure and applied mathematics before progressing to specialist topics and independent research.
At Lincoln, you'll learn in a supportive environment with access to dedicated mathematics facilities, experienced academics, and a course designed to prepare you for graduate careers where advanced analytical skills are in demand.
✔ Immerse yourself in a carefully curated programme
The mathematics degrees at Lincoln were designed by experts from academia and industry.
✔ Develop highly valued analytical skills
Mathematics graduates are sought after across industries because they can solve complex problems, interpret data, think logically, and plan critically.
✔ Learn how mathematics applies to the real world
Explore how tools from abstract algebra, mathematical modelling, statistics, computation, and analysis are used in finance, technology, science, engineering, and business.
✔ Build career-ready technical skills
Develop experience with mathematical software, programming, data analysis, and computational methods used by employers and researchers.
✔ Study in a supportive learning environment led by experts
You’ll be taught in smaller class settings than many larger universities, giving you greater access to academic support, feedback, and career guidance.
✔ Graduate with an integrated master’s qualification
The MMath programme allows you to study advanced mathematics and research-level topics in both pure and applied mathematics within a single degree.
✔ Gain strong preparation for postgraduate study or specialist careers
The advanced final year is ideal for students considering research, data-focused careers, or highly technical industries.
This course is designed to help you become a confident mathematician with the ability to apply advanced problem-solving skills in professional and research environments.
You’ll study areas including:
As you progress, you’ll move beyond formulas, and techniques to understanding how mathematics can be used to solve both abstract and practical problems across multiple scenarios and industries.
At Lincoln you may also have opportunities to:
The integrated master’s year allows you to deepen your expertise through advanced study and research-led learning, helping you stand out in competitive graduate markets.
Teaching on this course is delivered by academic staff who are active researchers in their fields. Our academics conduct cutting-edge research in both Pure and Applied Mathematics, including Algebra through the Charlotte Scott Centre and Computational Mathematics that models real-world problems. We collaborate with top research institutions in Australia, Brazil, Europe, South Africa, South Korea, and the USA, giving students an international, research-driven learning experience that is embedded at all levels of the programme.
This module begins with refreshing and expanding some of the material from the A-levels Maths, such as the binomial theorem, division of polynomials, polynomial root-finding, and factorisations. Then the Euclidean algorithm is introduced with some of its many applications, both for integers and for polynomials. This naturally leads to a discussion of divisibility and congruences, for integers and for polynomials, with emphasis on similarities and as a step towards abstraction.
This module focuses on the concepts of the derivative and the Riemann integral, which are indispensable in modern sciences.
Two approaches are used: both intuitive-geometric, and mathematically rigorous, based on the definition of continuous limits. Important results are the Mean Value Theorem, leading to the representation of some functions as power series (the Taylor series), and the Fundamental Theorem of Calculus which establishes the relationship between differentiation and integration. Further calculus tools are explored, such as the general properties of the derivative and the Riemann integral, as well as the techniques of integration. In this module, students may deal with many "popular" functions used throughout mathematics.
This module presents an introduction to computer packages for analytic formulas manipulation (computer algebra) and technical computing. Students will also have the opportunity to develop skills including; utilising a logbook as a factual record and as reflective self-assessment to support their learning.
The purpose of this module is to introduce students to basic mathematical reasoning such as rigorous definitions and proofs, logical structure of mathematical statements. Students will have the opportunity to learn the set-theoretic notation, get acquainted with various strategies of mathematical proofs such as proof by mathematical induction or proof by contradiction. Rigorous definitions of limits of sequences and functions will form a foundation for other courses on calculus and differential equations. The importance of definitions and proofs will be illustrated by examples of "theorems" which may seem obvious but are actually false, as well as certain mathematical "paradoxes".
This module describes vector spaces and matrices. Matrices are regarded as representations of linear mappings between vector spaces. Eigenvalues and eigenvectors are introduced, which lead to diagonalisation and reduction to other canonical forms. Special types of mappings and matrices (orthogonal, symmetric) are also introduced.
This module begins with an introduction of a probability space, which models the possible outcomes of a random experiment. Basic concepts such as statistical independence and conditional probability are introduced, with various practical examples used as illustrations. Random variables are introduced, and certain well-known probability distributions are explored.
Further study includes discrete distributions, independence of random variables, mathematical expectation, random vectors, covariance and correlation, conditional distributions and the law of total expectation. The ideas developed for discrete distributions are applied to continuous distributions.
Probability theory is a basis of mathematical statistics, which has so many important applications in science, industry, government and commerce. Students will have the opportunity to gain a basic understanding of statistics and its tools. It is important that these tools are used correctly when, for example, the full picture of a problem (population) must be inferred from collected data (random sample).
This module provides students the opportunity to learn a variety of transferable skills: to communicate scientific ideas via a variety of media, to work in groups, to manage and plan projects, to keep record of work.
Students have the opportunity to develop an understanding of general and specialized databases, their uses and searches. Group study can develop Students' skills in team-working around investigating a topic from literature. Students have the opportunity to take on administrative roles within the team and work towards common aims and objectives.
Data science is a field of study that utilises algorithms, statistics, and visualisation methods to answer scientific questions using data. In this module, students will learn how to load, transform, visualise, and extract knowledge from data using their skills as programmers. Students will also gain experience in using interactive programming environments (e.g. IPython/Jupyter) and open-source libraries (e.g., numpy, matplotlib, pandas) that are widely by data scientists in industry. During the module, students will work in groups to analyse a real-world dataset and present their findings to their peers.
This module introduces established theories describing optical, acoustic, and mechanical phenomena. The optics part includes Fermat’s principle of light propagation, Snell’s laws of reflection and refraction, thin lenses, and Huygens’s principle. The mechanics part includes the basic mathematical tools to describe the motion of objects (kinematics) and the laws of Newton (dynamics) underpinning these observed motions. The wave part of the module includes a discussion of propagating waves, the Doppler effect, phase and group velocities, and standing waves.
The concepts of groups, rings and fields are introduced, as examples of arbitrary algebraic systems. The basic theory of subgroups of a given group and the construction of factor groups is introduced, and then similar constructions are introduced for rings. Examples of rings are considered, including the integers modulo n, the complex numbers and n-by-n matrices. The ring of polynomials over a given field is studied in more detail.
Transmission of data may mean sending pictures from the Mars rover, streaming live music or videos, speaking on the phone, answering someone's question “do you love me?”. Problems arise if there are chances of errors creeping in, which may be catastrophic (say, receiving “N” instead of “Y”).
Coding theory provides error-correcting codes, which are designed in such a way that errors that occur can be detected and corrected (within certain limits) based on the remaining symbols. The problem is balancing reliability with cost and/or slowing the transmission. Students will have the opportunity to study various types of error-correcting codes, such as linear codes, hamming codes, perfect codes, etc., some of which are algebraic and some correspond to geometrical patterns.
Ideas of calculus of derivatives and integrals are extended to complex functions of a complex variable. Students will learn that complex differentiability is a very strong condition and differentiable functions behave very well. Integration along paths in the complex plane is introduced. One of the main results of this beautiful part of mathematics is Cauchy's Theorem that states that certain integrals along closed paths are equal to zero. This gives rise to useful techniques for evaluating real integrals based on the 'calculus of residues'.
Calculus techniques already provide solutions of simple first-order differential equations. Solution of second-order differential equations can sometimes be achieved by certain manipulations. Students may learn about existence and geometric interpretations of solutions, even when calculus techniques do not yield solutions in a simple form. This is a part of the existence theory of ordinary differential equations and leads to fundamental techniques of the asymptotic and qualitative study of their solutions, including the important question of stability. Fourier series and Fourier transform are introduced.
This module provides an introduction to the classical second-order linear partial differential equations and techniques for their solution. The basic concepts and methods are introduced for typical partial differential equations representing the three classes: parabolic, elliptic, and hyperbolic.
This module aims to provide students with the experience of working as part of a team on a project.
Students will have the opportunity to produce a set of deliverables relevant to their programme of study. Final deliverables will be negotiated between the group and their supervisor, the module coordinator will be responsible for ensuring that each project covers the learning outcomes of the module. Groups are expected to manage their own processes, and to hold regular meetings both with and without their supervisor. Groups will be allocated by the module coordinator and other members of staff. The process of development of the topic under study and the interaction and management of group members underpins the assessment of skills in the module.
Students have the opportunity to learn how mathematics is applied to modern industrial problems, and how the mathematical apparatus finds applications in the financial sector.
Students will have the opportunity to utilise computers for the numerical solution and simulation of models of physical and mathematical systems, including the use of computer procedural programming languages to solve computational problems.
Numerical algorithms will be introduced to exemplify key concepts in computational programming, with the emphasis on understanding the nature of the algorithm and the features and limitations of its computational implementation. In creating programs, the emphasis will be on using effective programming techniques and on efficient debugging, testing and validation methods. Students may also develop skills at using a logbook as a factual record and as reflective self-assessment to support their learning.
This module is concerned with a modern formulation of mechanics called Lagranian mechanics whereby the actually observed motion of an object is viewed as one among many potentially conceivable motions. The selection process of the actual motion satisfies the so-called Principle of Minimum Action. The corresponding formalism allows to tackle very intricate mechanical problems and has many technical advantages with regards to changes of variables. A ‘dual’ theory called Hamiltonian mechanics can also be formalized with its own advantages to address problems in mechanics. These two theories constitute the foundation on which quantum mechanics, statistical and quantum field theories are based. The module delivery includes the Minimum Action Principle, Euler-Lagrange equations, Noether’s theorem, Hamilton’s equations, and Poisson brackets
The module introduces the mathematical foundations of machine learning and the principled application of machine learning techniques to extract information and insights from data. It applies linear algebra and probability theory to introduce supervised and unsupervised learning methods. Students will gain the mathematical and practical skills needed to apply machine learning techniques to real-world data science problems.
This module provides an opportunity for students in the School of Engineering and Physical Sciences to spend a year abroad at one of the University’s partner institutions. During the year abroad, students share classes with students at their chosen destination and study on a suite of locally delivered modules. This module will extend the length of your programme by one year and is taken between level 5 (year 2) and level 6 (year 3).
This is a triple module in which a student undertakes an individual project under supervision of a research-active member of staff and during which the student is exposed to various research material and undertakes various tasks in relation to scientific communication. The individual project can be undertaken at an external collaborating establishment. Projects will be offered to students in a wide range of subjects aligned with their course specialism. The student will meet regularly with their supervisor in order to receive guidance and review progress.
Symmetry, understood in most broad sense as invariants under transformations, permeates all parts of mathematics, as well as natural sciences. Groups are measures of such symmetry and therefore are used throughout mathematics.
Abstract group theory studies the intrinsic structure of groups. The course begins with definitions of subgroups, normal subgroups, and group actions in various guises. Group homomorphisms are introduced and the related isomorphism theorems are proved. Sylow p-subgroups are introduced and the three Sylow theorems are proved. Throughout, symmetry groups are used as examples.
The module aims to equip students with knowledge of various numerical methods for solving applied mathematics problems, their algorithms and implementation in programming languages.
This module introduces the techniques of operational research - the mathematics of organisation. Students will learn a variety of optimisation techniques and will use these to solve applied problems, for example in transport and logistics. They will interpret the solutions, assess the advantages and disadvantages of different techniques and learn how to adapt a solution in response to new information.
This module gives a mathematical foundation of ideal and viscous fluid dynamics and their application to describing various flows in nature and technology.
Students are taught methods of analysing and solving equations of fluid dynamics using analytic and most modern computational tools.
This module is designed to provide students with an insight into the teaching of Mathematics at secondary school level.
The module aims to provide students with an opportunity to engage with cutting-edge maths education research and will examine how this research impacts directly on classroom practice. Students will have the opportunity to gain an insight into some of the key ideas in Mathematics pedagogy and how these are implemented in the school Mathematics lessons and will develop an understanding about the barriers to learning Mathematics that many students experience.
This module introduces key analytical techniques widely used in applied mathematics. It focuses on powerful methods for solving differential and integral equations, as well as the variational principles that underpin many scientific problems. Emphasis is placed on both theoretical understanding and practical problem-solving.
The reading module allows students the opportunity to acquire knowledge of a particular area of mathematics, and develop the skills needed to study mathematics in a more independent manner.
The module also provides an opportunity for Master's level students to study certain subjects in mathematics which may not be covered by any regular lecture modules, thus adding to the flexibility of the scheme of studies. Subject areas for proposed reading modules will be announced to students, together with an indicative syllabus. The choice offered will depend on the range of other lecture modules available to MMath students, as well as on the availability of teaching staff with particular areas of mathematical expertise, who could be able to act as moderators. The role of the reading module moderator is to provide students with support for their reading, including the setting of mathematical problems that are to be solved. The moderator also sets the written examination paper.
This module brings together the main ideas and methods of the mathematical theory of financial markets. In addition, the methods of practical calculations of volatilities of traded assets from historical data are discussed. The influence of randomness of the interest rate and volatilities on price of options is studied.
Lie algebras originated in the theory of continuous transformation groups as a means of introducing more linear structure and facilitate the classification of the so-called simple Lie groups. Theory of Lie algebras is now a well-established part of mathematics developing both in its own right and as a means of studying groups and even theoretical mechanics. This module deals with abstract Lie algebras.
Students will have the opportunity to learn the basic properties of various classes of Lie algebras, including soluble, nilpotent, semisimple, graded, etc. Important results on automorphisms and derivations of Lie algebras and the classification of finite-dimensional simple complex Lie algebras will be discussed.
In this quadruple module a student may undertake a substantial project under supervision of a research-active member of staff. Projects will be offered to students in a wide range of subjects, which will be assigned with account for student's individual preferences and programme of their studies. The project can be undertaken at an external collaborating establishment.
Students are expected to meet regularly with their supervisor in order to receive guidance and review progress. The project will result in a final written report/dissertation on a chosen mathematical area.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
This module begins with refreshing and expanding some of the material from the A-levels Maths, such as the binomial theorem, division of polynomials, polynomial root-finding, and factorisations. Then the Euclidean algorithm is introduced with some of its many applications, both for integers and for polynomials. This naturally leads to a discussion of divisibility and congruences, for integers and for polynomials, with emphasis on similarities and as a step towards abstraction.
This module focuses on the concepts of the derivative and the Riemann integral, which are indispensable in modern sciences.
Two approaches are used: both intuitive-geometric, and mathematically rigorous, based on the definition of continuous limits. Important results are the Mean Value Theorem, leading to the representation of some functions as power series (the Taylor series), and the Fundamental Theorem of Calculus which establishes the relationship between differentiation and integration. Further calculus tools are explored, such as the general properties of the derivative and the Riemann integral, as well as the techniques of integration. In this module, students may deal with many "popular" functions used throughout mathematics.
This module presents an introduction to computer packages for analytic formulas manipulation (computer algebra) and technical computing. Students will also have the opportunity to develop skills including; utilising a logbook as a factual record and as reflective self-assessment to support their learning.
The purpose of this module is to introduce students to basic mathematical reasoning such as rigorous definitions and proofs, logical structure of mathematical statements. Students will have the opportunity to learn the set-theoretic notation, get acquainted with various strategies of mathematical proofs such as proof by mathematical induction or proof by contradiction. Rigorous definitions of limits of sequences and functions will form a foundation for other courses on calculus and differential equations. The importance of definitions and proofs will be illustrated by examples of "theorems" which may seem obvious but are actually false, as well as certain mathematical "paradoxes".
This module describes vector spaces and matrices. Matrices are regarded as representations of linear mappings between vector spaces. Eigenvalues and eigenvectors are introduced, which lead to diagonalisation and reduction to other canonical forms. Special types of mappings and matrices (orthogonal, symmetric) are also introduced.
This module begins with an introduction of a probability space, which models the possible outcomes of a random experiment. Basic concepts such as statistical independence and conditional probability are introduced, with various practical examples used as illustrations. Random variables are introduced, and certain well-known probability distributions are explored.
Further study includes discrete distributions, independence of random variables, mathematical expectation, random vectors, covariance and correlation, conditional distributions and the law of total expectation. The ideas developed for discrete distributions are applied to continuous distributions.
Probability theory is a basis of mathematical statistics, which has so many important applications in science, industry, government and commerce. Students will have the opportunity to gain a basic understanding of statistics and its tools. It is important that these tools are used correctly when, for example, the full picture of a problem (population) must be inferred from collected data (random sample).
This module provides students the opportunity to learn a variety of transferable skills: to communicate scientific ideas via a variety of media, to work in groups, to manage and plan projects, to keep record of work.
Students have the opportunity to develop an understanding of general and specialized databases, their uses and searches. Group study can develop Students' skills in team-working around investigating a topic from literature. Students have the opportunity to take on administrative roles within the team and work towards common aims and objectives.
Data science is a field of study that utilises algorithms, statistics, and visualisation methods to answer scientific questions using data. In this module, students will learn how to load, transform, visualise, and extract knowledge from data using their skills as programmers. Students will also gain experience in using interactive programming environments (e.g. IPython/Jupyter) and open-source libraries (e.g., numpy, matplotlib, pandas) that are widely by data scientists in industry. During the module, students will work in groups to analyse a real-world dataset and present their findings to their peers.
This module introduces established theories describing optical, acoustic, and mechanical phenomena. The optics part includes Fermat’s principle of light propagation, Snell’s laws of reflection and refraction, thin lenses, and Huygens’s principle. The mechanics part includes the basic mathematical tools to describe the motion of objects (kinematics) and the laws of Newton (dynamics) underpinning these observed motions. The wave part of the module includes a discussion of propagating waves, the Doppler effect, phase and group velocities, and standing waves.
The concepts of groups, rings and fields are introduced, as examples of arbitrary algebraic systems. The basic theory of subgroups of a given group and the construction of factor groups is introduced, and then similar constructions are introduced for rings. Examples of rings are considered, including the integers modulo n, the complex numbers and n-by-n matrices. The ring of polynomials over a given field is studied in more detail.
Transmission of data may mean sending pictures from the Mars rover, streaming live music or videos, speaking on the phone, answering someone's question “do you love me?”. Problems arise if there are chances of errors creeping in, which may be catastrophic (say, receiving “N” instead of “Y”).
Coding theory provides error-correcting codes, which are designed in such a way that errors that occur can be detected and corrected (within certain limits) based on the remaining symbols. The problem is balancing reliability with cost and/or slowing the transmission. Students will have the opportunity to study various types of error-correcting codes, such as linear codes, hamming codes, perfect codes, etc., some of which are algebraic and some correspond to geometrical patterns.
Ideas of calculus of derivatives and integrals are extended to complex functions of a complex variable. Students will learn that complex differentiability is a very strong condition and differentiable functions behave very well. Integration along paths in the complex plane is introduced. One of the main results of this beautiful part of mathematics is Cauchy's Theorem that states that certain integrals along closed paths are equal to zero. This gives rise to useful techniques for evaluating real integrals based on the 'calculus of residues'.
Calculus techniques already provide solutions of simple first-order differential equations. Solution of second-order differential equations can sometimes be achieved by certain manipulations. Students may learn about existence and geometric interpretations of solutions, even when calculus techniques do not yield solutions in a simple form. This is a part of the existence theory of ordinary differential equations and leads to fundamental techniques of the asymptotic and qualitative study of their solutions, including the important question of stability. Fourier series and Fourier transform are introduced.
This module provides an introduction to the classical second-order linear partial differential equations and techniques for their solution. The basic concepts and methods are introduced for typical partial differential equations representing the three classes: parabolic, elliptic, and hyperbolic.
This module aims to provide students with the experience of working as part of a team on a project.
Students will have the opportunity to produce a set of deliverables relevant to their programme of study. Final deliverables will be negotiated between the group and their supervisor, the module coordinator will be responsible for ensuring that each project covers the learning outcomes of the module. Groups are expected to manage their own processes, and to hold regular meetings both with and without their supervisor. Groups will be allocated by the module coordinator and other members of staff. The process of development of the topic under study and the interaction and management of group members underpins the assessment of skills in the module.
Students have the opportunity to learn how mathematics is applied to modern industrial problems, and how the mathematical apparatus finds applications in the financial sector.
Students will have the opportunity to utilise computers for the numerical solution and simulation of models of physical and mathematical systems, including the use of computer procedural programming languages to solve computational problems.
Numerical algorithms will be introduced to exemplify key concepts in computational programming, with the emphasis on understanding the nature of the algorithm and the features and limitations of its computational implementation. In creating programs, the emphasis will be on using effective programming techniques and on efficient debugging, testing and validation methods. Students may also develop skills at using a logbook as a factual record and as reflective self-assessment to support their learning.
This module is concerned with a modern formulation of mechanics called Lagranian mechanics whereby the actually observed motion of an object is viewed as one among many potentially conceivable motions. The selection process of the actual motion satisfies the so-called Principle of Minimum Action. The corresponding formalism allows to tackle very intricate mechanical problems and has many technical advantages with regards to changes of variables. A ‘dual’ theory called Hamiltonian mechanics can also be formalized with its own advantages to address problems in mechanics. These two theories constitute the foundation on which quantum mechanics, statistical and quantum field theories are based. The module delivery includes the Minimum Action Principle, Euler-Lagrange equations, Noether’s theorem, Hamilton’s equations, and Poisson brackets
The module introduces the mathematical foundations of machine learning and the principled application of machine learning techniques to extract information and insights from data. It applies linear algebra and probability theory to introduce supervised and unsupervised learning methods. Students will gain the mathematical and practical skills needed to apply machine learning techniques to real-world data science problems.
This module provides an opportunity for students in the School of Engineering and Physical Sciences to spend a year abroad at one of the University’s partner institutions. During the year abroad, students share classes with students at their chosen destination and study on a suite of locally delivered modules. This module will extend the length of your programme by one year and is taken between level 5 (year 2) and level 6 (year 3).
This is a triple module in which a student undertakes an individual project under supervision of a research-active member of staff and during which the student is exposed to various research material and undertakes various tasks in relation to scientific communication. The individual project can be undertaken at an external collaborating establishment. Projects will be offered to students in a wide range of subjects aligned with their course specialism. The student will meet regularly with their supervisor in order to receive guidance and review progress.
Symmetry, understood in most broad sense as invariants under transformations, permeates all parts of mathematics, as well as natural sciences. Groups are measures of such symmetry and therefore are used throughout mathematics.
Abstract group theory studies the intrinsic structure of groups. The course begins with definitions of subgroups, normal subgroups, and group actions in various guises. Group homomorphisms are introduced and the related isomorphism theorems are proved. Sylow p-subgroups are introduced and the three Sylow theorems are proved. Throughout, symmetry groups are used as examples.
The module aims to equip students with knowledge of various numerical methods for solving applied mathematics problems, their algorithms and implementation in programming languages.
This module introduces the techniques of operational research - the mathematics of organisation. Students will learn a variety of optimisation techniques and will use these to solve applied problems, for example in transport and logistics. They will interpret the solutions, assess the advantages and disadvantages of different techniques and learn how to adapt a solution in response to new information.
This module gives a mathematical foundation of ideal and viscous fluid dynamics and their application to describing various flows in nature and technology.
Students are taught methods of analysing and solving equations of fluid dynamics using analytic and most modern computational tools.
This module is designed to provide students with an insight into the teaching of Mathematics at secondary school level.
The module aims to provide students with an opportunity to engage with cutting-edge maths education research and will examine how this research impacts directly on classroom practice. Students will have the opportunity to gain an insight into some of the key ideas in Mathematics pedagogy and how these are implemented in the school Mathematics lessons and will develop an understanding about the barriers to learning Mathematics that many students experience.
This module introduces key analytical techniques widely used in applied mathematics. It focuses on powerful methods for solving differential and integral equations, as well as the variational principles that underpin many scientific problems. Emphasis is placed on both theoretical understanding and practical problem-solving.
The reading module allows students the opportunity to acquire knowledge of a particular area of mathematics, and develop the skills needed to study mathematics in a more independent manner.
The module also provides an opportunity for Master's level students to study certain subjects in mathematics which may not be covered by any regular lecture modules, thus adding to the flexibility of the scheme of studies. Subject areas for proposed reading modules will be announced to students, together with an indicative syllabus. The choice offered will depend on the range of other lecture modules available to MMath students, as well as on the availability of teaching staff with particular areas of mathematical expertise, who could be able to act as moderators. The role of the reading module moderator is to provide students with support for their reading, including the setting of mathematical problems that are to be solved. The moderator also sets the written examination paper.
This module brings together the main ideas and methods of the mathematical theory of financial markets. In addition, the methods of practical calculations of volatilities of traded assets from historical data are discussed. The influence of randomness of the interest rate and volatilities on price of options is studied.
Lie algebras originated in the theory of continuous transformation groups as a means of introducing more linear structure and facilitate the classification of the so-called simple Lie groups. Theory of Lie algebras is now a well-established part of mathematics developing both in its own right and as a means of studying groups and even theoretical mechanics. This module deals with abstract Lie algebras.
Students will have the opportunity to learn the basic properties of various classes of Lie algebras, including soluble, nilpotent, semisimple, graded, etc. Important results on automorphisms and derivations of Lie algebras and the classification of finite-dimensional simple complex Lie algebras will be discussed.
In this quadruple module a student may undertake a substantial project under supervision of a research-active member of staff. Projects will be offered to students in a wide range of subjects, which will be assigned with account for student's individual preferences and programme of their studies. The project can be undertaken at an external collaborating establishment.
Students are expected to meet regularly with their supervisor in order to receive guidance and review progress. The project will result in a final written report/dissertation on a chosen mathematical area.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
Starting university can feel like a big step, especially if you’re choosing between several courses or universities. Lincoln aims to provide both academic and personal support throughout your degree.
Support may include:
The course is designed to help students gradually build confidence with advanced mathematical concepts while developing independent learning skills.
You’ll also become part of a university community where students can collaborate, share ideas, and support one another throughout their studies.
Mathematics graduates develop transferable skills that are valued in almost every sector. Employers actively seek graduates who can analyse information, solve problems, and work confidently with data.
What can you do with an MMath Mathematics degree?
Graduates may progress into careers such as:
Industries mathematics graduates work in
The advanced nature of the MMath qualification can also provide strong preparation for doctoral (PhD) research or specialist research roles.
For students who are still undecided about their career path, mathematics keeps your options open. The combination of analytical thinking, technical ability, and problem-solving skills is highly transferable and consistently valued by employers.
Gain hands-on experience in a real workplace and apply your learned skills in a professional setting.
Studying Mathematics at Lincoln is a way to learn more about a subject that has many applications within the real world, whilst also learning about theoretical Mathematics. It has helped me to grow as a mathematician.
William Evans
MMath Mathematics
This course could be a good fit if you:
You don’t need to have your entire career planned out before applying. Mathematics is one of the most flexible and respected degrees for students who want strong long-term career opportunities.
Our BSc programme currently meets the educational requirements of the Chartered Mathematician designation. This is awarded by the Institute of Mathematics and its Applications (IMA), when it is followed by subsequent training and experience in employment to obtain equivalent competences to those specified by the Quality Assurance Agency for taught Master’s degrees. The MMath programme is accredited by the IMA.
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112 to 120 UCAS Tariff points.
This must be achieved from a minimum of 2 A Levels or equivalent Level 3 qualifications, to include 40 points from Maths. For example:
A Level: BBC to BBB to include a Grade B in Maths
BTEC qualifications will be considered provided a grade B is obtained in A Level Maths.
T-level will be considered provided a grade B is obtained in A Level Maths.
Access to Higher Education Diploma: 112 to 120 UCAS points to be achieved from 45 Level 3 credits, including 40 points from 15 credits in Maths.
International Baccalaureate: 30 points overall to include a Higher Level in Maths.
GCSE's: Minimum of three at grade 4 or above, which must include English and Maths. Equivalent Level 2 qualifications may be considered.
The University accepts a wide range of qualifications as the basis for entry and do accept a combination of qualifications which may include A Levels, BTECs, Extended Project Qualification (EPQ).
We may also consider applicants with extensive and relevant work experience and will give special individual consideration to those who do not meet the standard entry qualifications.
Non UK Qualifications:
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages
https://www.lincoln.ac.uk/studywithus/internationalstudents/entryrequirementsandyourcountry/ for information on equivalent qualifications.
EU and Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-sessional English and Academic Study Skills courses.
For applicants who do not meet our standard entry requirements, our Science Foundation Year can provide an alternative route of entry onto our full degree programmes:
https://www.lincoln.ac.uk/course/sfysfyub/lifesciences/
If you would like further information about entry requirements, or would like to discuss whether the qualifications you are currently studying are acceptable, please contact the Admissions team on 01522 886097, or email admissions@lincoln.ac.uk
112 to 120 UCAS Tariff points from a minimum of 2 A Levels or equivalent Level 3 qualifications, to include 40 points from Maths.
If you are eligible for a contextual offer, a one grade or 8 UCAS Tariff point reduction to the standard entry requirements will be applied. Subject specific requirements will still be required as part of the standard entry criteria.
A Level: BBB to include a Grade B in Maths
BTEC qualifications will be considered provided a grade B is obtained in A Level Maths.
T-level will be considered provided a grade B is obtained in A Level Maths.
Access to Higher Education Diploma: 120 UCAS points to be achieved from 45 Level 3 credits, including 40 points from 15 credits in Maths.
International Baccalaureate: 30 points overall to include a Higher Level 5 in Maths.
GCSE's: Minimum of three at grade 4 or above, which must include English and Maths. Equivalent Level 2 qualifications may be considered.
The University accepts a wide range of qualifications as the basis for entry and do accept a combination of qualifications which may include A Levels, BTECs, Extended Project Qualification (EPQ).
We may also consider applicants with extensive and relevant work experience and will give special individual consideration to those who do not meet the standard entry qualifications.
Non UK Qualifications:
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages for information on equivalent qualifications.
EU and Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page.
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-sessional English and Academic Study Skills courses.
For applicants who do not meet our standard entry requirements, our Science Foundation Year can provide an alternative route of entry onto our full degree programmes:
If you would like further information about entry requirements, or would like to discuss whether the qualifications you are currently studying are acceptable, please contact the Admissions team on 01522 886097, or email admissions@lincoln.ac.uk
University Study is a major investment, so it’s important to understand the costs and support available. A full breakdown of the fees associated with this programme can be found below. Eligible students may be able to access scholarships and bursaries to help with study costs.
University Study is a major investment, so it’s important to understand the costs and support available. A full breakdown of the fees associated with this programme can be found below. Eligible students may be able to access scholarships and bursaries to help with study costs.
The best way to find out what it is really like to live and learn at Lincoln is to visit us in person. We offer a range of opportunities across the year to help you to get a real feel for what it might be like to study here.
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We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
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