Apologies for cross-posting.
A Research Associate in Bayesian Statistics is required to work on applying
Bayesian methods to some statistical models
which relate pressure to flow data for oil wells. These models have already
been constructed. The main task is computational:
to apply MCMC methods in order to obtain posterior distributions. The work
arises from a collaboration with the Department of Earth Science and
Engineering at Imperial College, London. Research there has focused on
developing statistical models for deconvolution of well-test data. For
background, see "From straight lines to deconvolution: the evolution of the
state of the art in well test analysis", February 2008, AC Gringarten, SPE
Reservoir Evaluation & Engineering.
This is a 9-month full-time fixed-term post. The research must start by
March 2009, preferably earlier.
Salary: £23,449 - £26,391 per annum, pro rata, depending on experience.
__________________________________________________________
Details:
Durham University is one of the UK's leading research-led universities, with
a strong commitment to both teaching and research. The Department of
Mathematical Sciences is a large Department, with an active programme of
internationally recognised research in a broad range of areas, and several
popular degree programmes with a very high quality student intake. The
Department has 65 academic staff, conducting internationally excellent
research in Pure Mathematics, Applied Mathematics, and
Statistics/Probability. There is a strong and active research environment,
with many visitors, seminars, international conferences and workshops, and
the Department benefits from excellent and fully supported computer and
library facilities. The Statistics Group has 13 academic staff and 21
postgraduate students. Areas of particular research interest include
Bayesian Statistics (with specific expertise in Bayes Linear Methods),
Applied Statistics (with specific attention to large-scale applications),
and Foundations of Statistics and Decision Theory (with specific attention
to generalised uncertainty quantification). These areas are combined in
ongoing research in large-scale applications, in particular in the area of
uncertainty in large-scale physical systems represented by computer models.
See http://www.dur.ac.uk/mathematical.sciences/stats/ for information about
the Statistics Group.
For informal queries, contact
David Wooff
(+44) 191 334 3121
[log in to unmask]
Application Process:
via
https://jobs.dur.ac.uk/default.asp
Job reference number: 2920
The university prefers to receive applications on-line. Please attach your
CV and a covering letter, giving details of how you match the person
specification. We can post a vacancy details pack (including application
form) to you, if you telephone our answering service on (+44) 191 334 6499
or e-mail: [log in to unmask]
Closing Date for Applications: 08/01/2009
Interview Date: 19/01/2009
-----------
David Wooff
Director, Statistics and Mathematics Consultancy Unit
& Senior Lecturer in Statistics, University of Durham
Department of Mathematical Sciences, Science Laboratories
South Road, Durham, DH1 3LE, UK.
email: [log in to unmask] Tel. 0191 334 3121, Fax 0191 334 3051.
Web: http://maths.dur.ac.uk/stats/people/daw/daw.html
|