Our MSc Industrial Mathematical Modelling provides a solid foundation in the core areas of mathematics relevant to industry.

Compulsory

Programming and Numerical Methods (15 credits)

The aim of this module is:

  • to introduce the basic concepts of programming on the practical level;
  • to introduce, explain, and implement numerical methods for solving ordinary and partial differential equations of industrial importance.

Mathematical Modelling I (15 credits)

The aims of this module are:

  • to develop skills in the mathematical modelling of real life situations;
  • to develop the ability to work effectively in a group.

Fluid Mechanics (15 credits)

The aim of this module is:

  •  to derive the fundamental equations of fluid mechanics;
  • to develop students' expertise in solving simplified forms of these equations applicable to a variety of fluid flows;
  • to learn about some industrial and environmental applications of fluid mechanics.

Optional

Functional Analysis (15 credits)

The aim of this module is to create awareness of the power and range of abstract mathematical concepts through a basic introduction to the methods of functional analysis.

Asymptotic Methods (15 credits)

The aims of this module are:

  • to introduce the concept of small and large parameters in equations and how they can be exploited to simplify difficult mathematical problems;
  • to introduce a wide range of approximation techniques to analyse differential equations and integrals.

Stochastic Models in Finance (15 credits)

The aim of this module is to:

  • to provide students with a rigorous mathematical introduction to the modern financial theory of security markets in discrete and continuous time models
  • to give students a solid theoretical background in the derivatives industry in discrete and continuous time models.

Compulsory

Theory of PDEs (15 credits)

The aims of this module are to gain familiarity with modern qualitative theory of linear PDE's with particular emphasis on second-order equations as well as to study selected aspects of modern methods for simple nonlinear PDEs.

Static and Dynamic Optimisation (15 credits)

The aim of this module is to gain familiarity with theory and techniques of static optimisation and dynamic optimisation.

Mathematical Modelling II (15 credits)

The aims of this module are:

  • to develop skills in the mathematical modelling of real life situations;
  • to develop the ability to work effectively in a group.

Optional

Spectral Theory (15 credits)

The aim of this module is to create awareness of the power and range of abstract mathematical concepts through a basic introduction to the methods of spectral theory.

Nonlinear Waves (15 credits)

The aims of this module are to:

  • introduce students to the main ideas and techniques of the modern theory of nonlinear waves;
  • demonstrate how these ideas and techniques can be used in a wide range of applications.

Statistics for Large Data (15 credits)

The aim of this module is

  • To introduce both supervised and unsupervised methods for learning from data.
  • To introduce methods of dimensionality reduction.
  • To introduce the R statistical programming language for implementing methods using real data.

Computational Methods in Finance (15 credits)

This module aims to

  • introduce numerical methods and associated theory for modelling of financial options;
  • teach students how to implement such numerical methods on computers;
  • gain experience in interpreting numerical results.

Compulsory

Industrial Modelling Research Project (60 credits)

The aim of this module is to give the students experience of independent work in mathematics and its applications, especially those of an industrial nature.