[alife] PhD Scholarship in Artificial Life

[Kevin Korb]

PhD opportunity in Artificial Life simulation
============================

PROJECT – Development of an ‘ageing household’ model for assessing
medium to long-term vaccine impact in populations. This is a joint
probject of The School of Population Health at the University of
Melbourne and the Clayton School of Information Technology at Monash
University. One PhD scholarship or scholarship top-up is available, to
support a candidate with skills relevant to either of the following
sub-projects:

a) A scholarship or scholarship top-up is being offered for a PhD
research candidate who will focus on data analysis and visualisation
of epidemiological agent-based simulations. The candidate will need
experience in applying existing visualisation techniques in 2 and 3D
and basic user-interface design principles to simulation
design. Experience with computer graphics programming in C or C++ and
OpenGL under Unix-based operating systems is required. Experience with
statistics or data analysis would be helpful; the ability to learn
such matters essential.

The research will extend basic visualisation techniques and adapt them
to the specifics of epidemiological simulation. In addition, it will
require the development of new, visually-guided ways to operate the
simulation software, understand its behaviour and communicate its
results. A willingness to experiment with sonification techniques to
assist in data-interpretation and simulation operation would be of
benefit.

OR:

b) A scholarship or top-up is being offered for a PhD research
candidate who will focus on understanding the influence of changing
population and household demography on the spread of infectious
diseases, and the length of time that vaccines given in infancy will
protect. The candidate will need undergraduate experience in public
health, epidemiology, biostatistics or demography. Applicants with a
background in computer science, physics, engineering or mathematics
with an interest in public health applications would also be
considered.

The research will involve collation and comparative analysis of
epidemiologic datasets from diverse populations, for estimation of
demographic transition and disease transmission parameters. The work
is part of a larger ARC-funded project seeking to investigate
interactions between temporal trends in demography and
infectious/communicable disease within agent-based model frameworks,
to which the student would contribute.

-- 
Dr Kevin Korb, Reader
School of Info Tech
Monash University
Clayton, Victoria 3800
http://www.csse.monash.edu.au/~korb