Research Fellows in Statistics and Biostatistics (3 positions)
Fixed-term, full-time for three years
You have a PhD in statistics, biostatistics, applied probability or aligned
discipline and a record of research publications. You are keen to join a
large team investigating new methodology for the analysis of data using
computational Bayesian and classical techniques, with application to
scientific areas including neurology, spatial ecology, bioinformatics,
infectious diseases, and human fertility.
Closes: 18 February 2005.
Salary: $58,510 $69,489
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Benefits available at QUT include up to 17% employer superannuation
contributions, a generous study assistance scheme, salary packaging,
relocation assistance (if applicable), extensive development and training
programs and access to a range of state-of-the-art facilities.
Applicants should clearly identify in their application if they have a
preference to be considered for a particular position in one of the three
specific areas of expertise.
Background Information
The three positions are located primarily in the School of Mathematical
Sciences at QUT’s Gardens Point campus, Brisbane. However, from time to
time the appointees for two of the positions may be required to work within
Brisbane hospitals that are participating as part of the collaborative
project. The positions will be responsible to Professor Tony Pettitt as
the Chief Investigator, however, the positions may have joint supervisory
responsibilities for each specific area of expertise. Ideally, the
appointees will have a PhD in statistics with a specialisation in Bayesian
statistics, and have computational skills in statistical software. The
School of Mathematical Sciences has a focus on applied statistical and
stochastic analysis with Professors Vo Anh, Kerrie Mengersen (ARC Centre of
Excellence Node in Bayesian Learning) and Adjunct Professor Malcolm Faddy.
There are three separate projects which form part of a suite of
collaborative projects involving applied statistics in a variety of
applications areas in collaboration with staff of hospitals in Brisbane
complemented by theoretical work undertaken in statistics through ARC
Discovery Grants.
Position 1: Research Fellow in Computational Bayesian Statistics
Duties include:
· Carry out research on a new three year ARC Discovery funded project
"Bayesian Statistical inference for Implicitly defined Probability
Models". The appointee will be responsible to Professors Tony Pettitt and
Malcolm Faddy.
· Carry out the analysis, writing up and publication of research.
· Present research results at workshops and conferences.
· Assist in the supervision of research students in project-related
areas.
· As necessary, assist in gaining further research funding for the
project.
· Maintain complete and accurate research records.
· Accountable for complying with health and safety policies,
procedures, hazard reporting and safe work practices.
· Maintain research confidentiality and conform to all requirements
for the protection of intellectual property.
SELECTION CRITERIA
Essential:
1. Completion of a PhD qualification in statistics, applied
probability or an aligned discipline such as machine learning.
2. Demonstrated ability to carry out research using modern
computational statistical techniques with an emphasis on Bayesian techniques.
3. Evidence of ability to carry out statistical research in various
scientific application areas.
4. Evidence of well developed written communication skills with a
proven track record of contributing to the publication of scientific
results in journals and other research publications.
5. Evidence of well developed communication skills, such as evidence
of conference presentation.
6. Evidence of ability to liaise effectively with a range of people.
7. Demonstrated ethical standards in research including an ability to
protect intellectual property.
Position 2: Research Fellow in Computational Bayesian Statistics (Motor
Unit Numbers Estimation)
Duties include
· Carry out research on a new three year ARC Linkage funded project
with the Royal Brisbane and Women’s Hospital called "Motor Unit Numbers
Estimation (MUNE) using Bayesian statistical methodology for monitoring the
progression of neuromuscular diseases”. This involves development of new
statistical methodology for applied Bayesian analysis involving
neuromuscular disease. The appointee will be responsible to Professor Tony
Pettitt and Dr Robert Henderson of Royal Brisbane and Womens Hospital.
· Be responsible for undertaking research activity on the ARC Linkage
funded project.
· Carry out the analysis, writing up and publication of research.
· Present research results at workshops and conferences.
· Assist in the supervision of research students in project-related
areas.
· As necessary, assist in gaining further research funding for the
project.
· Maintain complete and accurate research records.
· Liaising with the collaborating partner on the conduct of the
research project and assisting with some administrative matters; as
necessary be involved with the collection of clinical data.
· Accountable for complying with health and safety policies,
procedures, hazard reporting and safe work practices.
· Maintain research confidentiality and conform to all requirements
for the protection of intellectual property.
SELECTION CRITERIA
Essential:
1 Completion or near completion of a PhD qualification in Bayesian
statistics.
2 Demonstrated ability to carry out research using modern Bayesian
computational techniques with extensive knowledge of MCMC.
3 Evidence of well developed written communication skills with a
proven track record of contributing to the publication of scientific
results in journals and other research publications.
4 Evidence of well developed interpersonal communication skills with
the ability to liaise effectively with a range of people.
5 Evidence of the ability to present research at conferences and
workshops.
6 A capacity for the involvement in the collection of clinical data.
7 Maintain research confidentiality and conform to all requirements
for the protection of intellectual property.
Desirable
8 Knowledge of neurological science.
Position 3: Research Fellow in Biostatistics
A major project involving QUT mathematicians and statisticians and
infectious disease and intensive care clinicians at Princess Alexandra
Hospital and The Prince Charles Hospital has been funded by the ARC Linkage
Scheme. The chief investigators involve Professors Tony Pettitt, Sean
McElwain, Associate Professor Erhan Kozan and Dr Tony Morton. The
project’s aims include demonstrable improvements to health care for
patients in a hospital. Mathematical and statistical models are being
developed in the areas of infection control, surveillance and monitoring,
optimal allocation of scarce resources, such as intensive care beds, and
mathematical and statistical modeling of processes for the spread of
infectious diseases within hospitals. The appointee will provide high
level statistical research and some mathematical expertise to this project
working in the areas of mathematical and statistical modeling of infectious
diseases, development of statistical monitoring techniques for adverse
hospital events and biostatistical analysis. There are currently four
research students carrying out research on this project.
Duties include:
Undertaking research into algorithm development, novel statistical
methods and statistical computing methodology for the particular problems
which occur in the collaborative project: for adverse hospital event
monitoring, the development of control chart and surveillance methodology
and its implementation; for hospital acquired infectious diseases, design
of studies for and analysis of disease transmission processes.
Undertaking research activity on other defined projects within the
scope of the project, such as biostatistical modeling for clinical studies.
Actively participating in research collaborations with the
industry partners.
Contributing to the supervision of research students and junior
research assistants employed on the projects.
Carry out the analysis, writing up and publication of research.
Present research results at workshops and conferences.
Participating in conferences and supporting and participating in
short courses and other training avenues as appropriate.
Liaising with the collaborating partners on the conduct of the
research project and assisting with some administrative matters.
Accountable for complying with health and safety policies,
procedures, hazard reporting and safe work practices.
Maintain research confidentiality and conform to all requirements
for the protection of intellectual property.
SELECTION CRITERIA
Essential:
Completion of a PhD qualification in applied or theoretical statistics,
applicable mathematics or biomathematics.
Proven ability to carry out successful, high quality, independent research
work in consultation with project leaders.
Demonstrated experience or capacity to develop skills in supervision of
research projects and research staff.
Demonstrated experience in or capacity to develop skills in Bayesian
statistical methodology.
Evidence of computational skills in statistical/mathematical software such
as R, Matlab.
Proven ability to work independently in a research environment.
Proven skills in collaborating with statistics, mathematical, operations
research and clinical researchers.
Proven ability to prepare and communicate the aims and outputs of research
projects in a range of formats including formal and informal oral
presentations, refereed research papers and reports.
Desirable:
1. Experience in statistical monitoring and surveillance techniques
and biostatistics.
2. Skills in mathematical modelling, optimisation or similar linked areas.
Smoking is not permitted in QUT buildings, inside QUT vehicles or in any
area not designated as a smoking area.
FURTHER INFORMATION: Before submitting an application, applicants should
refer to all additional information listed on this page regarding
conditions of employment, applying for positions and information about the
University. For further clarification about these positions, after reading
the selection criteria and duty statement, contact Professor Tony Pettitt
on (07) 3864 2309, e-mail: [log in to unmask] If you require further
information on conditions of employment contact the Human Resources
Department on (07) 3864 4144 or e-mail: [log in to unmask]
APPLICATIONS: Applications and envelopes should quoting . Applicants are
encouraged to systematically address the selection criteria and include
evidence of academic qualifications and experience plus the names, address
(postal and/or e-mail), phone and fax numbers of three referees.
Applications should reach the Associate Director, HR Client Services, QUT,
GPO Box 2434, Brisbane, Qld. 4001 by 18 February 2005. QUT is an equal
opportunity employer.
Professor Tony Pettitt
Head School of Mathematical Sciences
Queensland University of Technology
GPO Box 2434
Brisbane 4001
Queensland
+61 (0)73864 2309
Fax +61 (0)73864 2310
See for papers www.maths.qut.edu.au/~pettitt
See for bio www.maths.qut.edu.au/profiles/pettitt/
CRICOS No. 00213J
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