Mathematics MSc Programmes

Study Programme

Information about the Computational Applied Mathematics MSc study programme.

Outline

The programme consists of 120 credits of courses in total during Semesters 1 and 2, followed by a 60 credit dissertation which is completed during the Summer. The courses taken will be dependent on the availability of courses each year which may be subject to change as curriculum develops to reflect a modern degree programme. 

Semester 1

The first semester is composed of a combination of compulsory and optional courses. The compulsory courses will build strong applied mathematical and computational foundations. The curriculum is completed with optional courses in related subjects such as statistics and optimization.

Semester 2

The second semester is again composed of a combination of compulsory and optional courses, building on the skills gained in Semester 1. The compulsory courses include Research Skills, which will prepare you for the Summer Dissertation Project.  The optional courses cover a wide range of areas including, for example, data science, high performance computing, and related disciplines such as Informatics and Physics.

Dissertation

The 60 credit individual dissertation will take the form of a supervised research-style project on a topic proposed by a staff member of the Applied and Computational Mathematics group. The aim of the project is to provide practical experience and skills for tackling scientific problems which require both computational approaches and mathematical insight. This will include identifying and applying appropriate mathematical and numerical techniques, interpreting the results, and presenting the conclusions. For 2017-18 the likely course structure is as follows:

Proposed compulsory courses for the programme include

  • Applied Dynamical Systems (10 credits, Semester 1)
  • Mathematics of Data Assimilation (10 credits, Semester 1)
  • Object-Oriented Programming with Applications (10 credits, Semester 1)
  • Scientific Computing (10 credits, Semester 1)
  • Numerical Partial Differential Equations with Applications (10 credits,
  • Semester 2)
  • Research Skills for Computational and Applied Mathematics (20 credits, Semester 2)
  • Dissertation (CAM) (60 credits, Semester 2 onwards)

Proposed optional courses for the programme include

  • Applied Stochastic Differential Equations (10 credits, Semester 1)

  • Fundamentals of Optimization (10 credits, Semester 1)

  • Numerical Linear Algebra and Applications (10 credits, Semester 1)

  • Statistical Programming (10 credits, Semester 1)

  • Python Programming (10 credits, Semester 1)

  • Mathematics in Action A/B (10 credits, Semester 2, the 'A' and 'B' courses are offered in alternate years)

  • Multi-scale Methods in Mathematical Modelling (10 credits, Semester 2)

  • Numerical Ordinary Differential Equations with Applications (10 credits, Semester 2)

  • Data Analytics with High Performance Computing (10 credits, Semester 2)

  • Large Scale Optimization for Data Science (10 credits, Semester 2)

  • Optimization Methods in Finance (10 credits, Semester 2)

  • A range of courses from Mathematics, Informatics or Physics (10 credits, Semester 2)