SCHOOL OF PHYSICAL SCIENCES
Cross-entropy Methods in
Complex Biological Systems
The Cross-Entropy (CE) method
provides a powerful new way to find superior solutions to
complicated optimisation problems in biology, ranging from
better design and implementation of medical treatments to an
increased understanding of complex ecosystems. Dr Dirk Kroese
is one of the pioneers of the CE method.
This position,
which is supported by the Australian Research Council, offers
a unique opportunity to further enhance the theory and
application scope of the CE method, by focusing on
applications in Computational Biology. The successful
applicant will work closely with Drs Dirk Kroese and Jonathan
Keith. The role of the Postdoctoral Research Fellow will be
to undertake a detailed implementation of stochastic
optimization methods and to conduct various numerical
experiments that will contribute to the theoretical
development of the CE ideas.
Applicants must have a
selection of advanced skills in computing, simulation,
probability/statistics, optimization, graph theory, and
preferably have some knowledge of biological systems. A PhD
in a relevant topic is essential.
This is a full-time
fixed term position for three years available from late
February 2005 until 31 December 2007 (this is negotiable),
with the possibility of renewal subject to funding. The
position is open to Australian and international
candidates. The remuneration package will be in the range of
$52,930 - $64,466 per annum, which includes employer
superannuation contributions of 17% of salary.
The
the position description and selection criteria are available
online at http://www.uq.edu.au/jobs/2004documents/epsa/1299732.doc
For further information, please visit http://www.maths.uq.edu.au/~kroese
or contact Dr Dirk Kroese by email (kroese@maths.uq.edu.au) or telephone ((07) 3365 3287).
Send applications to:
Dr Dirk
Kroese
Mathematics
The University of Queensland
St Lucia QLD 4072
Australia
Or e-mail kroese@maths.uq.edu.au
Closing date for applications: 31 January 2005
Reference Number: 1299732