MSc Operational Research with Risk
Why Operational Research with Risk?
Risk analysis deals with the assessment and management of risk from unlikely but costly or distressing events. Risk management is becoming an increasingly important subject, partly due to the focus of the media on large disasters and the resulting threat of litigation. As a result most large organisations are now active in producing and maintaining formal risk management strategies, and this provides significant employment opportunities. This MSc will give an Operational Research perspective on risk and risk management.
Structure and course options for the Operational Research with Risk MSc programme
You will take 120 credits of courses in total during Semesters 1 and 2, followed by a 60 credit dissertation which you complete over the summer. The courses you take will be dependent on the availability of courses each year which may be subject to change as the curriculum develops to reflect a modern degree programme.
Compulsory courses cover the core skills of operational research, with most compulsory courses being studied in Semester 1. All courses are worth 10 credits, unless otherwise indicated.
Semester 1 compulsory courses have previously included:
- Fundamentals of Operational Research
- Fundamentals of Optimization
- Methodology, Modelling and Consulting Skills
- Stochastic Modelling
Semester 2 compulsory courses have previously included:
- Simulation
For your MSc to have a specialization in Risk, you must also study at least two of the following Semester 2 courses:
- Credit Scoring
- Optimization Methods in Finance
- Topics in Applied Operational Research
- Operational Research in the Energy Industry
You will have the opportunity to tailor your degree by selecting from a broad range of optional courses. All courses are worth 10 credits, unless otherwise indicated.
Semester 1 optional courses have previously included:
- Statistical Methodology
- Incomplete Data Analysis
- Python Programming
- Statistical Programming
- Introductory Probability and Statistics
- Introduction to Practical Programming with Objects
Semester 2 optional courses have previously included:
- Machine Learning in Python
- Algorithmic Game Theory and its Applications
- The Analysis of Survival Data
- Time Series
- Large Scale Optimization for Data Science
- Generalised Regression Models
- Integer and Combinatorial Optimization
The project gives you the opportunity to apply skills developed earlier to real operational research problems. Projects often take the form of a consultancy exercise for a sponsoring organisation. Projects usually involve modelling the problem and applying existing packages and/or developing a computer program for a new application of operational research. It is also possible to have an academic project without a direct link to an external organisation.
Academic projects are defined and supervised inside the department. External projects are defined by some external organisation, which may be an industrial or commercial company, a government body or research lab. There will be one supervisor in the University and one in the outside organisation. In an external organisation, you may work as part of a team on a project, but the work you do must be sufficiently self-contained that it can be written up into a coherent dissertation.
The purpose of the external placement is to enhance your experience through working on a practical project, and to allow you to apply and extend the knowledge and skills that you have already developed as part of your MSc programme. You will also develop your communication and other transferable skills, and interact with others on a more open-ended problem than you will have experienced in the taught part of the MSc.