MPhil Operational Research
Our MPhil Operational Research gives you the opportunity to explore areas where optimisation and mathematical modelling are important. These include logistics, revenue management, networks and stochastic control; areas of great practical interest and use in the public and private sectors. Our projects often have an experimental aspect which is underpinned by forefront mathematical and computational research in these areas.
Our staff are strongly committed to research and teaching. They have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals such as; International Journal of Mathematics in Operational Research, Transportation Science, Journal of the Operational Research Society, Mathematical Problems in Engineering, and European Journal of Operational Research.
Our Department of Mathematical Sciences is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
- Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
- We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
- We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
- Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
- Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
Our MPhil Operational Research gives you the opportunity to explore areas where optimisation and mathematical modelling are important. These include logistics, revenue management, networks and stochastic control; areas of great practical interest and use in the public and private sectors. Our projects often have an experimental aspect which is underpinned by forefront mathematical and computational research in these areas.
Our staff are strongly committed to research and teaching. They have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals such as; International Journal of Mathematics in Operational Research, Transportation Science, Journal of the Operational Research Society, Mathematical Problems in Engineering, and European Journal of Operational Research.
Our Department of Mathematical Sciences is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
- Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
- We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
- We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
- Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
- Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
