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Operational Research with Risk - MSc/PgDip


Course Description

This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Operational Research (OR) is an important skill that is in high demand.

This MSc will give an Operational Research perspective on risk and its management.

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses have previously included:

  • Computing for OR and Finance
  • Fundamentals of Optimization
  • Fundamentals of OR
  • Methodology, Modelling and Consulting Skills
  • Probability and Statistics
  • Simulation
  • Stochastic Modelling

Option courses are generally grouped into the following areas:

  • Finance
  • Industry
  • Optimization
  • Statistics

As part of your option course choices Operational Research with Risk requires you to study a combination from a set of courses which, previously, has included

  • Credit Scoring
  • Stochastic Optimization
  • The Analysis of Survival Data
  • Statistical Modelling
  • Risk Analysis

Career opportunities

The skills you will learn are in demand by a vast range of high-profile organisations including consultancy firms, companies with operational research departments such as airlines or telecommunications providers, financial firms and the public sector.

Recent graduates have joined British Airways, the Government OR Service, Barclays, Deloitte, Capgemini and smaller specialised OR, finance and energy companies.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.


Visit the Operational Research with Risk - MSc/PgDip page on the University of Edinburgh website for more details!

Entry Requirements

At least a UK 2:1 degree, or its international equivalent, in a numerate discipline such as mathematics, engineering, computer science, physical or biological sciences, economics or business.

Last Updated

02 May 2017

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