Higher degree research

Higher degree research

The Department of Statistics offers programs leading to the following postgraduate research degrees:

Programs may be taken either by full-time or by part-time study and arrangements may be made under certain conditions for supervision of research to be conducted externally.

Student research projects

Student Course Supervisor/s Thesis title
Christopher Anderson MSc;STAT Julian Leslie
Andrzej Kozek
The Importance of Line Width Measurements in Discriminating between Pencil Types in Forensic Handwriting Investigations
Adrian Barker PhD;STAT Andrzej Kozek
Nino Kordzakhia
Non-parametric statistical methods in optimal portfolio selection
Hilary Green PhD;STAT Peter Petocz
Don McNeil
The use of colour as a variable in statistical graphs
Eliud Kangogo PhD;STAT A/Prof. Andrzej
S. Kozek
Prof. Barry Quinn
Robust Statistical techniques to estimate the parameters of heavy-tailed distributions
Annette Kifley PhD;STAT Gillian Heller Statistical methods and issues in analysis of health – related trade offs
Braddon Lance PhD;STAT Graham Wood Sequential comparative modelling of tertiary protein structure
Alex Moore PhD:STAT Peter Petocz Bayesian Stochastic search for group level parameters in a discrete choice system
Timothy Peters PhD;STAT David Bulger Selection of Microarray Elements for Optimal Linear Discrimination with Potential Application in Cancer Therapy
Sheenal Srivastava PhD;STAT Professor Graham Wood
Dr. Jonathan Ellis
A Study of Rules for Cotranslational Protein Structure Formation
Kenny Xu PhD;STAT Jun Ma
Tania Prvan
Proportional and other Semi-Parametric Hazard Models Fitting by Directly Maximizing the Penalized Likelihood

Recent completions

Student Course Supervisor/s Thesis title
Kenneth Beath PhD;STAT Gillian Heller
Malcolm Hudson
Latent variable models of infant growth
Karol Binkowski PhD;STAT Andrzej Kozek
Nino Kordzakhia
Application of levy processes in optimal portfolio selection
Shanley Chong

Suicide patterns in Australia, Canada and United States: Statistical Analysis (Awarded 2007)
Fabien Huard PhD;STAT Prof. Graham Wood
Andrzej Kozek
Investigation of the sequential aspect in protein folding
Siew Vui Dorothy Wong PhD;STAT Graham Wood
Kehui Luo
Multivariate Methods for the Analysis of Genomic and Proteomic Data
Sibba Gudlaugsdottir PhD;STAT Graham Wood
Jun Ma
Modelling the origin of introns
Peter Humburg PhD;STAT David Bulger Tiling Arrays
Ling Li PhD;STAT Jun Ma
Malcolm Hudson
Stephane Heritier
Julian Leslie
Aggregated analysis for multivariate medical data
Zhixin Liu PhD;STAT Jun Ma
Malcolm Hudson
Val Gebski
Statistical models for recurrent events data: with application to study of radiotherapy re-treatment in lung cancer patients.
Rachel O’Connell PhD;STAT Malcolm Hudson Development and assessment for prognostic indices for assessing risk
Sangdao Wongsai PhD;STAT Peter Petocz Statistical Analysis for Waterborne Hazard to Human Health
Duangdaw Sirisatien PhD;STAT Prof. Graham Wood Optimal Animal Nutrition

How to apply

For all research degrees, supervision must be available and candidates can be accepted only where suitable specialised supervision is available. Candidates should check the research interests of members of the department and approach potential supervisors prior to making application to the university.

Prospective candidates should also contact the Department’s Research Degree Co-ordinator Associate Professor Jun Ma for discussion prior to filling out an application.

You can also visit the Higher Degree Research Office (HDRO) section for more information, entry requirements and how to apply.

Further Enquiries

Associate Professor Jun Ma
Phone: (02) 9850 8548
Email: jun.ma@mq.edu.au

For more information about Higher Degree Research and Research Training Pathways contact our HDR Office or call us at +61 2 9850 7987.

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