*Apologies for cross-listing*

DEPT. OF MANAGEMENT SCIENCE
STRATHCLYDE BUSINESS SCHOOL
Glasgow, UK

*Note this studentship is available to UK students only.*

A PhD studentship is available in the area of Operational Research, in the Department of Management Science, Strathclyde Business School, starting October 2013.  The successful candidate will work on a research project entitled ‘Computationally Efficient Decision Support for Strategic Dynamic Bayesian Network Models’ under the supervision of Professors John Quigley and Lesley Walls.  Applications will be considered until 15 June 2013, or until a suitable candidate is found thereafter.
With 12 full-time and 3 part-time academic staff, 5 postdoctoral research associates and more than 30 PhD students, the Department of Management Science (http://www.strath.ac.uk/mansci/) has a lively research environment with several groups and themes.  Being part of a prestigious triple-accredited business school, the department has an applied focus with a substantial number of industrial collaborations.

PROJECT SUMMARY
Strategic Dynamic Bayesian Networks (SDBN) represent a new form of modelling motivated by the need to address decisions problems, such as the design of a resilient supply. SDBN models formally incorporate the optimal decisions of multiple decision-makers as well as modelling the temporal dynamics of the interactions between these decisions and the realisation of uncertainties.  A major challenge in operationalizing SDBN lies in the computational complexities required if these models are to be applied to large complex networks. This projects aims to address two gaps in knowledge.
Research Challenge 1: To reduce the cognitive elicitation burden placed on experts in populating SDBN models, we seek to develop an algorithm that iterates between eliciting expert judgment and a mathematical evaluation of such data.
Research Challenge 2: To provide optimal decision support for large, complex networks, we seek to develop computationally efficient methods of obtaining accurate inference for the SDBN.
This research is novel and exciting because SDBN are in their infancy and show great potential to be applied within a cooperative game theory framework. The development of more efficient algorithms requires use of novel methods within Graph Theory which are ripe for translation to this new context.

REQUIREMENTS/ELIGIBILITY
This is an EPSRC funded studentship and as such only available to UK students.
Candidates are required to have an excellent Honours (Undergraduate) degree in a numerical subject, including but not limited to Operational Research, Mathematics, Computer Science, Engineering or Economics.  Candidates with a Masters degree (or equivalent) will be strongly preferred.
Mathematical and analytical skills are essential for the project.  Computing skills (in particular programming skills in C/C++ or similar) are highly desirable.

DURATION AND SALARY
This PhD studentship is for 3 years with a starting date of October 2013.  The progress of the successful candidate is subject to standard annual and interim reviews.  The studentship fully covers the tuition fees for the 3-year duration and provides an annual tax-free stipend of £14,000 to the sucessful candidate.

HOW TO APPLY & INFORMAL ENQUIRIES
All applications are to be made online at http://pgr.strath.ac.uk/  to the Department of Management Science.  All documents (including scans of original documents) can be uploaded during the online application process.  Candidates are expected to submit a cover letter, a research proposal detailing their 3-year plan, CV, any university degree certificates and transcripts, English test results (if applicable), two recommendation letters (or contact details of two referees, if letters are not available to them), and any other supporting documents.  In order to be considered for this studentship, candidates should specifically note the title of this project in their online application when prompted about funding and their source of finance.
For informal enquiries, contact Professor John Quigley (http://www.strath.ac.uk/mansci/staff/quigleyjohnprof/) or Professor Lesley Walls (http://www.strath.ac.uk/mansci/staff/wallslesleyprof/).