Fully funded Ph.D. position available within the School

Ph.D. project
Interactive representations of uncertainty for modern statistical inference
Closing date: 1st June 2014

In many scientific areas the exploration of the uncertainty of parameters or quantities of interest is as important as estimating the individual effects. A careful assessment of uncertainty using statistical modelling lends support to a scientific analysis. But such assessments can be limited by the use of static summaries for data and statistical model parameters, which cannot capture the space of variations or the sensitivity of model elements to change. Interactive exploration of uncertainty, while more computationally intensive, can afford investigation of otherwise difficult-to-perceive interactions and relationships between quantities of interest, and can generate new scientific hypotheses. This Ph.D. project will propose and investigate methods for effective interactive exploration of uncertainty in data and statistical model output suited to large sensor networks.

Candidates should have an excellent single or combined degree in Statistics or Computing Science and have strong computational and mathematical modelling skills. Excellent written and oral communication skills, and strong time-management skills are also desirable.

The College of Science and Engineering at the University of Glasgow is investing in interdisciplinary research on sensors and sensor systems. This exciting project will be co-supervised by academics from the Schools of Computing Science, and Mathematics and Statistics.

The studentship covers fees and a stipend (at UK and EU student levels). The stipend is based on the UK Research Council rates and the studentship will be of 3.5 years duration.

For further information, please contact:
Dr. John Williamson (jhw@dcs.gla.ac.uk)
Prof. Adrian Bowman (adrian.bowman@glasgow.ac.uk)
Prof. Peter Craigmile from Ohio State University will also be a collaborator on the project.