MSc in Financial and Computational Mathematics

Our postgraduate Financial and Computational Mathematics programme equips graduates with the skills necessary to pursue a successful career in quantitative finance. Modern financial technology is based upon sophisticated computational techniques for the modelling of asset and market movements, and the valuation of financial derivatives. This course provides a solid grounding in computational finance along with machine learning techniques and includes a team-based research project with opportunities to work with our industry partners. Past graduates of this programme have been recruited to risk management (Acadia, China Reinsurance Corporation), regulatory (FinTru, KBRA), and wealth managmentinvestment roles (Fidelity). They have also progressed to SFI-funded study at PhD level in the application of machine learning to finance. This programme will prepare you for a broad spectrum of roles in the financial sector and particularly in quantitative finance, risk analysis, and investment banking.

Candidates must have obtained at least a 2.2 degree or equivalent in the mathematical sciences or another quantitative subject.Candidates who have obtained at least a 2.2 honours degree in Engineering or Physics will be considered and should be able to demonstrate to the Course Coordinator some prior experience of probability and statistics, linear algebra, multivariate calculus, ordinary differential equations, and programming.All candidates must be ultimately approved by the Course Coordinator.