This degree will provide you with the general research skills required to carry out independent work. The course comprises introductory training in research skills and the study of an appropriate subject area. The greater part of it is devoted to project work. The course improves your chances of promotion if you are already working in the field and gives a sound training for a career in research and design in the area of applied and computational mathematics.
You can take the degree full-time over one or two years, or part-time over between 18 and 36 months.
In common with our taught MSc courses the total course is valued at 180 credits at Masters level, this being made up of taught modules and a project, with a single module valued at 12 credits and based on a notional 96 hours of student effort, which includes class contact, private study and assessment. The class contact time is normally 30 hours, which for those attending in the evenings is equivalent to one evening a week over a ten week term.
The minimum period of full-time registration is 12 months, maximum 24 months; for part-time students the periods are 18 months and 36 months, respectively.
For the MSc by Research in Applied Mathematics the course structure adopted consists of three components:
1. A 12 credits core study skills module. This module consists of five units:
* Information Search and Retrieval
* Project Management
* Research Roles and Principles
* Legislation: Intellectual Property and Health and Safety
* Presentation Skills
2. One 24-credit module suitable for the topic of MSc by research. The module will be specified when you register for the course and selected to give coverage for related studies essential to the successful completion of the course. Assessment is by in-course evaluation of set coursework assignments, together with examinations in most modules at the end of the teaching block. The modules must be passed.
3. A research project. Normally this will be rated at 144 credits at M-level. The nature of the project is different from an MPhil and PhD project in that it will be primarily of an investigative or scholarly nature, with possibly limited innovating elements. It is expected to be more extensive and show greater depths of originality and insight than the dissertation for a taught Masters degree.
The project will normally be formulated, including specification of objectives, in consultation between yourself and your nominated Director of Studies. Where the project is able to be pursued (wholly or partially) within an industrial organisation then, where appropriate, a representative of that organisation should be involved in the formulation of the project.
On completion of the project you will present a written report (thesis) and defend it at an oral examination (viva voce). The thesis should demonstrate your knowledge and understanding of the subject and should satisfy the agreed objectives.
While registered on this course you will be a member of the Applied Mathematics Research Centre. Supervision will be provided by staff associated with the research centre; all of whom have an established research record and supervisory experience to, and including, PhD level.
There will be either one or two supervisors for each research project. One will be identified as the Director of Studies, with the specific responsibility to ensure that you receive proper guidance and support. Where the project is linked to an external organisation (eg work based) use of a second supervisor from that organisation will be encouraged.
Areas of Research
The Applied Mathematics Research Centre carries out a considerable amount of fundamental research alongside applied research, of direct interest to industry, in the general area of mathematical modelling and analysis of engineering components.
Current research activities include:
* Boundary Integral Equations
* Composite Materials
* Condensed Matter Physics
* Conformal Maps
* Continuum Mechanics
* Finite Difference Methods
* General Relativity
* Inverse Scattering Problems
* Lattice Field Theory
* Liquid Crystals
* Machine Learning
* Nonlinear dispersive Waves
* Partial Differential Equations
* Soft Condensed Matter
* Statistical Physics