Candidates should have:
A good Honours degree (minimum 2:1) and/or a Master’s degree in a quantitively focused subject area (e.g. economics, management science, statistics, mathematics, engineering.)
- They may also have appropriate experience or other skills which are relevant to this project. Relevant skills could include experience developing reliability models, spatial analysis models, experience in the energy sector, etc.
- As well as a CV and relevant qualification transcripts, applications must be accompanied by a cover letter indicating how their skills and experience would contribute to this project.
- Two references are required, of which at least one should be from an academic.
Often in risk analysis we do not have sufficient data on which to develop a suitable model for supporting decision analysis and so we rely on expert judgment. Bayesian methods provide a rich framework in which we can blend expert judgement with empirical data to refine the former and enhance our ability to anticipate the future. This project is concerned with developing decision support in supply chain risk analysis and we seek to develop appropriate methods for eliciting and structuring expert judgement, as well as statistical model development to explicate the relationship between risk mitigation strategies and key performance indicators.
We are seeking a candidate with a quantitative background. This project is sponsored by an industrial partner and will involve both theoretical and applied research.
Informal enquiries to either email@example.com or firstname.lastname@example.org
Admin enquiries to Alison Kerr email@example.com
How to apply
Applications to: Alison Kerr (Alison.firstname.lastname@example.org)