With digital technologies driving advances in many aspects of the modern world, there is growing demand for graduates with combined skills in mathematics and computer science across a wide range of sectors.
This Integrated Master's programme provides students with opportunities to advance their understanding in both fields, and emphasises the bridges between theory and practice.
Students are encouraged to develop a broad knowledge and skills base that is suitable for computer and IT-related posts across a range of sectors, as well as research and analytical roles.
Students are able to personalise the degree by choosing the modules that best align with their career aspirations or areas of interest. Individual and group projects during the course are designed to develop transferable skills.
This integrated Master's degree (MSci) offers students the opportunity to continue their study for an additional year at an advanced level, examining topics in greater depth and undertaking substantial, additional project work.
With digital technologies driving advances in many aspects of the modern world, there is growing demand for graduates with combined skills in mathematics and computer science across a wide range of sectors.
This Integrated Master's programme provides students with opportunities to advance their understanding in both fields, and emphasises the bridges between theory and practice.
Students are encouraged to develop a broad knowledge and skills base that is suitable for computer and IT-related posts across a range of sectors, as well as research and analytical roles.
Students are able to personalise the degree by choosing the modules that best align with their career aspirations or areas of interest. Individual and group projects during the course are designed to develop transferable skills.
This integrated Master's degree (MSci) offers students the opportunity to continue their study for an additional year at an advanced level, examining topics in greater depth and undertaking substantial, additional project work.
Subject ranked in the top 10 in the UK for student satisfaction*
Institute of Mathematics and its Applications (IMA) accreditation
Informed by cutting-edge research
Guest speakers from around the world
Additional problem-solving tutorials
Placement Year available
*Complete University Guide 2025 (out of 62 ranking institutions).
This joint honours degree aims to offer a broad education in applied and pure mathematics, coupled with the opportunity to develop the analytical and problem-solving skills associated with computer science. The programme provides students with opportunities to advance their understanding in both fields and emphasises the bridges between theory and practice.
Students have the chance to learn from, and work alongside, our team of academics. They can support and encourage them to apply imagination, creativity, and rigour, to the solution of real-world problems.
In the first year students have the chance to benefit from an additional three hours per week of problem-solving tutorials. During the first year of the programme, the School of Mathematics and Physics also runs a tutor system, providing one hour weekly tutor sessions in small groups.
The course is taught via lectures, problem-solving classes, computer based-classes and seminars.
This joint honours degree aims to offer a broad education in applied and pure mathematics, coupled with the opportunity to develop the analytical and problem-solving skills associated with computer science. The programme provides students with opportunities to advance their understanding in both fields and emphasises the bridges between theory and practice.
Students have the chance to learn from, and work alongside, our team of academics. They can support and encourage them to apply imagination, creativity, and rigour, to the solution of real-world problems.
In the first year students have the chance to benefit from an additional three hours per week of problem-solving tutorials. During the first year of the programme, the School of Mathematics and Physics also runs a tutor system, providing one hour weekly tutor sessions in small groups.
The course is taught via lectures, problem-solving classes, computer based-classes and seminars.
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 introduces the fundamentals of computer hardware. You will be provided with the knowledge of how core computer components function and how they come together to form a single system. The module will introduce data representation and digital logic, followed by a study of the Central Processing Unit, memory, interconnections and I/O devices. Standard, sequential (i.e. von Neumann) architecture will be compared to modern hardware platforms that are based on multi-core processors, parallel units and embedded systems.
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 extends the concepts and practice of simple computer programming, with attention paid to the essentials that constitute an object-oriented computer program including layout, structure, and functionality. The module aims to extend students' knowledge of computer programming and introduces them to the object-oriented paradigm and related concepts applied to algorithm and software development. There is also emphasis upon the use of version control and its role in archiving and facilitating software development.
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 introduces students to software constructs and the development of simple programs using a high-level programming language. Simple design concepts and standard programming practices are presented, and attention is paid to the fundamentals that constitute a complete computer program including layout, structure, and functionality. Additionally, the fundamental computing data structures allowing the representation of data in computer programs are explored and implemented.
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.
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 will explore the ‘full stack’ of web application technologies. You will have the opportunity to learn how to design and develop both the frontend and backend of modern web applications. The module aims to cover the three-tier architecture approach for developing web applications: i) presentation tier, ii) application tier, and iii) data tier. You can learn how to use the relevant technologies for each tier, encompassing web presentation, application programmable interfaces (APIs), and database technologies. The overall aim of the module is for you to learn the how to develop robust client-server applications using secure and scalable technologies.
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.
This module provides students with the opportunity to develop knowledge of the processes and principles of Human-Computer Interaction (HCI) and User Experience Design (UXD) starting with a history and overview of the role HCI in furthering the field of computer science. The module will guide students through notions of usability and accessibility, user-centred design and requirements analysis, prototyping, statistical analysis, and qualitative evaluation using state of the art methods and techniques. The professional, ethical, social, and legal issues in designing and studying interactive technology will be considered throughout.
The field of software development is continuously evolving, driven in part by the increasing usage of generative AI and the requirement to protect applications from sophisticated cyber-attacks. This module aims to introduce students to modern development practices. Students will gain hands-on experience in tools and practices used for secure application development, deployment and monitoring.
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.
This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social, and ethical implications of cyber security.
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.
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.
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from raw images and interpret the result.
The module introduces the fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
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.
This module aims to equip you with the skills to design and develop connected, data-driven mobile applications, leveraging smartphone sensor technologies such as location, camera and proximity sensors. Consuming RESTful web services will be an area of focus for the data driven components of mobile app development. You can utilize contemporary tools to build mobile applications by applying industry-standard techniques for both code-base development and user-centered design.
The module aims to equip students with knowledge of various numerical methods for solving applied mathematics problems, their algorithms and implementation in programming languages.
Parallel Programming is an important modern paradigm in computer science, and a promising direction for keeping up with the expected exponential growth in the discipline. Executing multiple processes at the same time can tremendously increase computational throughput, not only benefiting scientific computations, but also leading to new exciting applications like real-time animated 3D graphics, video processing, and physics simulation. The relevance of parallel computing is especially prominent due to availability of modern, affordable computer hardware utilising multi-core and/or large number of massively parallel units.
This module offers students the chance to demonstrate their ability to work independently on a significant, in-depth project requiring the coherent and critical application of computer science theory and skills.
Students must initially produce a project proposal and related materials to frame the work, specifying clear, specific, academically justified, and appropriately scoped aims and objectives, as well as feasible means for fulfilling those aims and objectives. Students then work independently to fulfil those project goals. Throughout this process students are expected to demonstrate the application of practical development and analytical skills, innovation and/or creativity, and the synthesis of information, ideas and practices to generate a coherent problem solution.
This module introduces tensors, which are abstract objects describing linear relations between vectors, scalars, and other tensors. The module aims to equip students with the knowledge of tensor manipulation, and introduces their applications in modern science.
This module aims to cover the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents.
Search is introduced as a unifying framework for Artificial Intelligence (AI), followed by key topics including blind and informed search algorithms, planning and reasoning, both with certain and uncertain (e.g. probabilistic) knowledge. Practical exercises in AI programming will complement and apply the theoretical knowledge acquired to real-world problems.
This module aims to explore advanced topics using a contemporary object-oriented programming language. The objective is to prepare students for professional-level programming in scientific and commercial computing, and to support programming tasks in other modules of this award.
Students can explore a range of programming topics through a series of lectures and practical workshops, and will work on producing an individual programming assignment.
In this quadruple module a student undertakes 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 independently conduct a substantial research in modern mathematical/computational science working in a research group of the school, university or an external collaborating establishment.
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 introduces the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments. Students are introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops. Working at Master's level, students can research the area in depth and produce critical reports of their findings.
The module introduces the fundamentals of data science and big data analytics, an emergent specialised area of computer science that is concerned with knowledge on ‘Big Data’ mining and visualisation, including state-of-the-art database platforms, development toolkits, and industrial and societal application scenarios. Students can explore core Big Data analytics concepts and models, the current technology landscape, and topical application scenarios using a variety of simulation environments and open datasets.
This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social, and ethical implications of cyber security. As a Master's level module students are also encouraged to consider current research in the field of cyber security.
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.
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.
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from raw images and interpret the result.
The module introduces fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
This module is designed to provide students with an insight into the teaching of Mathematics at secondary school level and does this by combining university lectures with an experience of a placement in a secondary school Mathematics department.
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.
The module aims to equip students with methods to analyse and solve various mathematical equations found in physics and technology.
Parallel Computing is an important modern paradigm in computer science. Executing multiple processes at the same time can tremendously increase the computational throughput, not only benefiting scientific computations, but also leading to new exciting applications like real-time animated 3D graphics, video processing, and physics simulation. The relevance of parallel computing is especially prominent due to availability of modern, affordable computer hardware utilising multi-core and/or large number of massively parallel units.
† 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 introduces the fundamentals of computer hardware. You will be provided with the knowledge of how core computer components function and how they come together to form a single system. The module will introduce data representation and digital logic, followed by a study of the Central Processing Unit, memory, interconnections and I/O devices. Standard, sequential (i.e. von Neumann) architecture will be compared to modern hardware platforms that are based on multi-core processors, parallel units and embedded systems.
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 extends the concepts and practice of simple computer programming, with attention paid to the essentials that constitute an object-oriented computer program including layout, structure, and functionality. The module aims to extend students' knowledge of computer programming and introduces them to the object-oriented paradigm and related concepts applied to algorithm and software development. There is also emphasis upon the use of version control and its role in archiving and facilitating software development.
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 introduces students to software constructs and the development of simple programs using a high-level programming language. Simple design concepts and standard programming practices are presented, and attention is paid to the fundamentals that constitute a complete computer program including layout, structure, and functionality. Additionally, the fundamental computing data structures allowing the representation of data in computer programs are explored and implemented.
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.
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 will explore the ‘full stack’ of web application technologies. You will have the opportunity to learn how to design and develop both the frontend and backend of modern web applications. The module aims to cover the three-tier architecture approach for developing web applications: i) presentation tier, ii) application tier, and iii) data tier. You can learn how to use the relevant technologies for each tier, encompassing web presentation, application programmable interfaces (APIs), and database technologies. The overall aim of the module is for you to learn the how to develop robust client-server applications using secure and scalable technologies.
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.
This module provides students with the opportunity to develop knowledge of the processes and principles of Human-Computer Interaction (HCI) and User Experience Design (UXD) starting with a history and overview of the role HCI in furthering the field of computer science. The module will guide students through notions of usability and accessibility, user-centred design and requirements analysis, prototyping, statistical analysis, and qualitative evaluation using state of the art methods and techniques. The professional, ethical, social, and legal issues in designing and studying interactive technology will be considered throughout.
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.
This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social, and ethical implications of cyber security.
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.
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.
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from raw images and interpret the result.
The module introduces the fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
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.
This module aims to equip you with the skills to design and develop connected, data-driven mobile applications, leveraging smartphone sensor technologies such as location, camera and proximity sensors. Consuming RESTful web services will be an area of focus for the data driven components of mobile app development. You can utilize contemporary tools to build mobile applications by applying industry-standard techniques for both code-base development and user-centered design.
The module aims to equip students with knowledge of various numerical methods for solving applied mathematics problems, their algorithms and implementation in programming languages.
Parallel Programming is an important modern paradigm in computer science, and a promising direction for keeping up with the expected exponential growth in the discipline. Executing multiple processes at the same time can tremendously increase computational throughput, not only benefiting scientific computations, but also leading to new exciting applications like real-time animated 3D graphics, video processing, and physics simulation. The relevance of parallel computing is especially prominent due to availability of modern, affordable computer hardware utilising multi-core and/or large number of massively parallel units.
This module offers students the chance to demonstrate their ability to work independently on a significant, in-depth project requiring the coherent and critical application of computer science theory and skills.
Students must initially produce a project proposal and related materials to frame the work, specifying clear, specific, academically justified, and appropriately scoped aims and objectives, as well as feasible means for fulfilling those aims and objectives. Students then work independently to fulfil those project goals. Throughout this process students are expected to demonstrate the application of practical development and analytical skills, innovation and/or creativity, and the synthesis of information, ideas and practices to generate a coherent problem solution.
This module introduces tensors, which are abstract objects describing linear relations between vectors, scalars, and other tensors. The module aims to equip students with the knowledge of tensor manipulation, and introduces their applications in modern science.
This module aims to cover the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents.
Search is introduced as a unifying framework for Artificial Intelligence (AI), followed by key topics including blind and informed search algorithms, planning and reasoning, both with certain and uncertain (e.g. probabilistic) knowledge. Practical exercises in AI programming will complement and apply the theoretical knowledge acquired to real-world problems.
This module aims to explore advanced topics using a contemporary object-oriented programming language. The objective is to prepare students for professional-level programming in scientific and commercial computing, and to support programming tasks in other modules of this award.
Students can explore a range of programming topics through a series of lectures and practical workshops, and will work on producing an individual programming assignment.
In this quadruple module a student undertakes 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 independently conduct a substantial research in modern mathematical/computational science working in a research group of the school, university or an external collaborating establishment.
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 introduces the main concepts of Autonomous Mobile Robotics, providing an understanding of the range of processing components required to build physically embodied robotic systems, from basic control architectures to spatial navigation in real-world environments. Students are introduced to relevant theoretical concepts around robotic sensing and control in the lectures, together with a practical “hands on” approach to robot programming in the workshops. Working at Master's level, students can research the area in depth and produce critical reports of their findings.
The module introduces the fundamentals of data science and big data analytics, an emergent specialised area of computer science that is concerned with knowledge on ‘Big Data’ mining and visualisation, including state-of-the-art database platforms, development toolkits, and industrial and societal application scenarios. Students can explore core Big Data analytics concepts and models, the current technology landscape, and topical application scenarios using a variety of simulation environments and open datasets.
This module provides an understanding of the challenges in cyber security faced by society and industry. This includes an examination of the impact of threats and develops an understanding of mechanisms to reduce the risk of attack. The module examines a range of cyber threats and attack types and introduces strategies to mitigate these. It also prompts students to consider the legal, social, and ethical implications of cyber security. As a Master's level module students are also encouraged to consider current research in the field of cyber security.
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.
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.
Digital image processing techniques are used in a wide variety of application areas such as computer vision, robotics, remote sensing, industrial inspection and medical imaging. Image processing is the study of algorithms that take images as an input and return information about these images. This module aims to provide a broad introduction to the field of image processing, culminating in a practical understanding of how to apply and combine techniques to various image-related applications. Students will have the opportunity to extract useful data from raw images and interpret the result.
The module introduces fundamentals of machine learning and principled application of machine learning techniques to extract information and insights from data. The module covers supervised and unsupervised learning methods. The primary aim is to provide students with knowledge and applied skills in machine learning tools and techniques which can be used to solve real-world data science problems.
This module is designed to provide students with an insight into the teaching of Mathematics at secondary school level and does this by combining university lectures with an experience of a placement in a secondary school Mathematics department.
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.
The module aims to equip students with methods to analyse and solve various mathematical equations found in physics and technology.
Parallel Computing is an important modern paradigm in computer science. Executing multiple processes at the same time can tremendously increase the computational throughput, not only benefiting scientific computations, but also leading to new exciting applications like real-time animated 3D graphics, video processing, and physics simulation. The relevance of parallel computing is especially prominent due to availability of modern, affordable computer hardware utilising multi-core and/or large number of massively parallel units.
† 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.
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.
The course is assessed through a variety of means, including tests, course work, examinations, written reports, and oral presentations. The weighting given to each assessment method may vary across each academic year. The University of Lincoln aims to ensure that staff return in-course assessments to students promptly.
The course is assessed through a variety of means, including tests, course work, examinations, written reports, and oral presentations. The weighting given to each assessment method may vary across each academic year. The University of Lincoln aims to ensure that staff return in-course assessments to students promptly.
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 MSci programme is accredited by the IMA.
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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 combined degree comprises some of the most industry-relevant and interesting modules, which are cherry-picked from the two disciplines.
Nick Short
BSc (Hons) Mathematics and Computer Science
Students on this course are encouraged to obtain and undertake work placements independently in the UK or overseas during their studies, providing hands-on experience in industry. These can range from a few weeks to a full year if students choose the sandwich year option. Placements may be conducted with external research institutions (which can be overseas). The option is subject to availability and selection criteria set by the industry or external institution. A Placement Year Fee is payable to the University of Lincoln during this year for students joining in 2025/26 and beyond. Students are expected to cover their own travel, accommodation, and living costs.
Graduates may choose to use their problem-solving and analytical skills to develop careers in areas such as research, IT, science, education, consultancy, finance, business, and industry in the UK and overseas. Some may go on to undertake further study at postgraduate level. Additionally, transferable skills such as communications, problem-solving, and decision-making, which students are expected to develop throughout their studies, are valuable in many spheres of employment.
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.
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
Please note application assessment criteria may vary by country and we may close to applications from some domiciles. Please view the Your Country pages of our website before making an application.
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
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.
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
Please note application assessment criteria may vary by country and we may close to applications from some domiciles. Please view the Your Country pages of our website before making an application.
Going to university is a life-changing step and it's important to understand the costs involved and the funding options available before you start. A full breakdown of the fees associated with this programme can be found on our course fees pages.
For eligible undergraduate students going to university for the first time, scholarships and bursaries are available to help cover costs. To help support students from outside of the UK, we are also delighted to offer a number of international scholarships which range from £1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
Going to university is a life-changing step and it's important to understand the costs involved and the funding options available before you start. A full breakdown of the fees associated with this programme can be found on our course fees pages.
For eligible undergraduate students going to university for the first time, scholarships and bursaries are available to help cover costs. To help support students from outside of the UK, we are also delighted to offer a number of international scholarships which range from £1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
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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