Hi,
The closing dates for the University of Southampton and the University of
Glasgow EPSRC funded postdoc positions are now both on 29th June 2012. There
is only just over a week to go before the closing date.
Thanks
Duncan
In the UK, air pollution is estimated to reduce average life expectancy by
around 6 months, with corresponding equivalent health cost of £19 billion
annually. Estimation of the effects of air pollution on human health is a
complex task for a number of reasons: misalignment of health and air
pollution data in both space and time; the existence of spatio-temporal
correlation; and the presence of confounding factors. The Engineering and
Physical Sciences Research Council is funding a large interdisciplinary
project to develop statistical methodology to address these issues. The main
goal of the project is to combine spatio-temporal models for pollution and
health data into a single large hierarchical Bayesian model. Two Research
Fellow (RF) positions in Statistics are available as part of this exciting
collaborative project, which will involve air quality modellers, climate
scientists, epidemiologists and statisticians at the Universities of
Southampton and Glasgow, and at the Met Office. One RF position will be
within the Southampton Statistical Sciences Research Institute (S3RI) and
Mathematics at the University of Southampton and the second position will be
in the School of Mathematics and Statistics at the University of Glasgow.
Applicants for the positions should have, or be about to obtain, a PhD in
statistics, or have equivalent research experience. Preference will be given
to applicants with a background in Bayesian statistical modelling,
especially spatial/spatio-temporal modelling, and Markov chain Monte Carlo.
The RF in Southampton will be supervised by Dr Sujit Sahu while the RF in
Glasgow will be supervised by Dr Duncan Lee and Prof Richard Mitchell. Both
fellows will work closely with each other and the project partners. In
addition, they will benefit from advice from the Visiting Researcher on the
project, Prof Alan Gelfand (Duke University, USA).
The main role of the Southampton RF will be to develop new statistical
methodology for estimating uncertainty in the levels of major air
pollutants, and in an aggregate index, under spatial and temporal
misalignment of multivariate data and at multiple resolutions. Work with
Glasgow will then develop a single integrated Bayesian framework for
combining pollution and health models. Informal enquiries regarding this
position may be made to Dr Sujit Sahu, telephone +44 (0) 23 8059 5123,
email: [log in to unmask]
The main role of the Glasgow RF will be to develop new statistical
methodology to capture the spatio-temporal correlation structure in
areal-unit health data, utilising Gaussian Markov Random Field models and
then to work with Southampton on the integrated model. Informal enquiries
regarding this position may be made to Dr Duncan Lee, telephone +44 (0) 141
330 4047, email: [log in to unmask]
Both the positions are fixed-term for 3 years and will commence on 1st
October 2012, or as soon as possible thereafter. The appointed salary will
be determined by the relevant University, depending on the successful
candidate's skills and experience. The closing date for applications is 29th
June, 2012 for the Southampton position, and 29th June 2012 for the Glasgow
position. Interviews are likely to be held in the week beginning July 2,
2012. Candidates who wish to apply for both positions should submit separate
applications to each university with a clear statement of their preference,
if any. To apply for the Southampton post, please visit www.jobs.soton.ac.uk
or alternatively telephone 023 8059 2750 for an application form. Please
quote vacancy reference number 119712WT on all correspondence. To apply for
the Glasgow post please visit http://www.gla.ac.uk/about/jobs/
job reference number E20219.
------ End of Forwarded Message
You may leave the list at any time by sending the command
SIGNOFF allstat
to [log in to unmask], leaving the subject line blank.
|