Course details

Study options

Full-time: 1 - 2 years, Part-time:

UK fee

£850 per 20 credits* (2019/20)

International fee

£14,250 for the full programme (2019/20)

Course level




Start dates

January, September


Markeaton Street, Derby Campus

Course description

Our MSc delivers an outstanding combination of advanced application-oriented mathematical concepts and computational methodologies. Broad in scope and genuinely multidisciplinary in nature, it is based on solid and well-founded mathematical theory.

The subject modules are carefully designed to be accessible to anyone with a good first degree in mathematics or in science and engineering subjects which have a strong mathematical component.

Comprising three key stages – a Postgraduate Certificate, a Postgraduate Diploma and a full MSc qualification – the programme will give you:


What you will study

This course is made up of three stages – Postgraduate Certificate, Postgraduate Diploma and MSc.

You will study modules such as:


This module develops your knowledge, understanding and ability to implement a diverse range of optimisation techniques, reflecting current research activity. Many problems that cannot be solved by classical methods can be investigated and solved using modern optimisation techniques. The theoretical background, key results and applications are presented through numerous examples. Optimisation techniques are implemented using relevant mathematical software.

Scientific Computing

The aim of this module is to develop the reflective and practical understanding of computational techniques in mathematics. It will give you an insight into the main computational techniques and their practical implementation to address relevant mathematical models and their applications. A variety of numerical methods and techniques will be discussed, including numerical solutions of linear systems and numerical integrations, as well as ordinary and partial differential equations.

Studying at Masters Level and Research Methods

This module aims to develop your ability to study at masters level and to develop, plan and execute a project using the processes of research. This module is a prerequisite for undertaking the masters dissertation (Independent Scholarship).

You will study modules such as:

Networks and Algorithms

We will develop your knowledge and understanding of challenging topics in graph theory, networks and algorithms. Relevant and up-to-date applications in the simulation of complex networks, for example social networks and computer networks, will give you skills for today's working environment in an increasingly complex networked world. The topics chosen will lead to, or reflect, current research activity and give you a solid basis for further study at higher levels.

Non-linear System Dynamics

The overall aim of this module is to enhance your skills in the analysis and applications of non-linear ordinary differential equations (ODEs). Such equations are relevant to a wide range of physical systems, and the subject area is an important one in the context of system modelling. The techniques studied are both quantitative and qualitative in nature, and the module examines different types of non-linear equations and techniques for both their analysis and solution.

You will be exposed to a variety of theoretical and applicable aspects of topics through a combination of formal lectures and tutorial sessions. Any computational requirements will be met by our existing software resources to facilitate problem solving and consolidate understanding of the subject matter. Our computing facilities will support the use of numerical/symbolic programming languages.

Stochastic Processes

This module builds upon fundamental knowledge of elementary probability concepts and develops the foundations for modelling random phenomena mathematically, in particular the mathematical description of systems’ time evolution by stochastic processes. Based on an introduction to the general concepts of stochastic processes, the major focus is on Markov chains. We present analytical, numerical and simulative methods for analysing Markov models arising in application domains.

You will study one module, such as:

Independent Scholarship

This module provides the opportunity for you to consolidate and extend your understanding, skills and knowledge of your subject area as developed through stages 1 and 2 of the programme. The aim is to ensure that you can formulate and tackle research questions competently, efficiently, independently, and with relevance to a particular problem and/or application.

How you will learn

You will study a wide range of topics on the themes of optimisation, scientific computing, stochastic processes, networks and algorithms, and non-linear system dynamics. The programme will also give you an insight into research methods and you will analyse a topic in depth for your dissertation.

The course features a stimulating combination of lectures, seminars, tutorials and practical project work to give you a real breadth and depth of knowledge in applied mathematics and computation.

Assessments on this course are principally based on coursework, which gives you the opportunity to investigate relevant topics independently.

Entry requirements

You'll usually need:

Fees and funding

2019/20 Fees (August 2019 - July 2020)


£850 per 20 credits*

£850 per 20 credits*


£14,250 for the full programme


*Note – at postgraduate level, you’ll need to gain the following number of credits in total to obtain the awards below.

Postgraduate Certificate60 Credits
Postgraduate Diploma120 Credits
MA or MSc180 Credits

This means you will gain 180 credits in total to complete the full MA or MSc. If you are studying part time you will normally complete your studies over two or three years, depending on the course structure.

Please note that all fees may be subject to annual increase.

Additional costs and optional extras

How to apply


In our increasingly complex networked world – where innovative technologies are constantly emerging – the skills you will develop on this MSc programme are particularly valuable to prospective employers.

Computational mathematics is relevant to almost every science, engineering, business and finance discipline as well as many industrial sectors. With this qualification, you will be able to communicate your knowledge to professionals from diverse backgrounds and will show that you can operate within – and lead – multidisciplinary teams.

Studying for the MSc is also an excellent preparation for academic research in any area where computational techniques play a significant role. It offers a clear route to further study at PhD level.

Programme leader

Dr Ovidiu Bagdasar

Contact us


If you need any more information from us, eg on courses, accommodation, applying, car parking, fees or funding, please contact us and we will do everything we can to help you.

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† Additional information about your studies

Part time study options also available.

Download programme specification

Teaching hours

Like most universities, we operate extended teaching hours at the University of Derby, so contact time with your lecturers and tutors could be anytime between 9am and 9pm. Your timetable will usually be available on the website 24 hours after enrolment on to your course.

Additional costs and optional extras

We’re committed to providing you with an outstanding learning experience. Our expert teaching, state-of-the-art facilities and great employability prepare you for your future career. As part of our commitment to you we aim to keep any additional study costs to a minimum. However, there are occasions where students may incur some additional costs.

Included in your fees

Mandatory costs not included in your fees

Optional costs not included in your fees

Please note: Our courses are refreshed and updated on a regular basis. If you are thinking about transferring onto this course (into the second year for example), you should contact the programme leader for the relevant course information as modules may vary from those shown on this page.