PhD Top-Up Scholarships in Applied Statistics or Bioinformatic

Contacts:

Dr Kim-Anh Le Cao:   k.lecao@qfab.org;

Dr Dominique Gorse: d.gorse@qfab.org;

Dr Kathy Ruggiero:    k.ruggiero@auckland.ac.nz

Webpages:     http://qfab.org

                        http://www.imb.uq.edu.au

                        http://www.math.univ-toulouse.fr/~biostat/mixOmics

Purpose of the scheme

The Queensland Facility for Advanced Bioinformatics (QFAB, University of Queensland) associated with Wound Management Innovation CRC offers an annual ‘top-up’ scholarship to a student holding either an Australian Postgraduate Award (APA) or equivalent award for full-time research in Applied Statistics leading to the award of a PhD. This award is to be used for research within the research project of the CRC (see attached PDF for more information on the research project).

In 2010, two top-up scholarship in applied statistics and bioinformatics will be awarded.

Eligibility

• Prospective PhD candidates applying for an APA or equivalent award with strong undergraduate academic training in the field of Applied Statistics or Bioinformatics  are eligible to apply. The PhD research project must fit into the research project of Wound Management Innovation CRC.

• Part-time PhD candidates are not eligible to apply.

Details of the Award

Scholarship top-up will be awarded on the basis of academic excellence, the quality of the applicant’s curriculum vitae, references from senior colleagues in the field and the likelihood of the applicant’s future involvement in the Wound Management Innovation CRC research project.

The scholarship top-up is awarded for up to 3 years and consists of an annual stipend from $7,000 up to a $10,000 for a full time applicant – subject to qualifications to supplement a basic postgraduate scholarship (eg an APA or equivalent award). As a full-time scholarship top-up award, it is non-taxable. Applicants may apply for a maximum extension of the top-up award of up to six months, in line with an extension of their primary award. Extensions may be approved subject to satisfactory progress, provided the grounds are related to their research and are beyond the control of the student.

An allowance of up to $5,000 per annum will be available, subject to satisfactory subject, to attend and participate in national and international conferences.

Top-up scholarship holders are expected to be involved in the Wound Management Innovation CRC research project, i.e. develop appropriate statistical methodologies and bioinformatics tools for the integration and the interrogation of biological and clinical data from the CRC. 

Project Description

QFAB and the Wound Management Innovation CRC are looking for two PhD candidates in the field of Applied Statistics and Bioinformatics to develop statistical methodologies and bioinformatics tools to analyze high throughput biological data sets from the Wound Management Innovation CRC project.

The research questions

Recent advances in ‘omics’ technologies now enable quantitative monitoring of the abundances of various biological molecules in a high-throughput manner and thereby enable the determination of the variation between different biological states on a genomic scale. Popular ‘omics’ platforms include transcriptomics, which measures mRNA transcript levels, proteomics, which quantifies protein abundances, and metabolomics, which determine abundances of small cellular metabolites, amongst others (interactomics, fluxomics). However, no single ‘omics’ analysis can fully unravel the complexities of molecular biology. The integration of multiple layers of information is therefore crucial to better understand biological systems.

Data integration is a challenging task due to the high dimensionality of the data as well as their heterogeneous nature. Variable selection, i.e. co-jointly selecting the relevant and informative genes, metabolites, proteins, etc., is therefore essential to obtaining biologically meaningful information from the data. Some attempts have been made recently to perform variable selection and integrate heterogeneous data sets. Approaches such as the ones developed in the mixOmics R package (Le Cao et al., 2009b), for example, have demonstrated the important role of such tools in assisting biologists to characterize complex biological systems (Le Cao et al, 2008, 2009a).

There is also a need to develop public data repositories to share collected data, as they often contain useful information beyond that for which it was originally collected. This would enable new hypotheses to be generated and eventually derive useful information from the data collected. The databases not only have a storage function, but should also be jointly analyzed by sophisticated computational and visualization tools available for data interpretation.

The Wound Management Innovation CRC research project will provide the unique opportunity to have access to such high throughput data and will allow the PhD candidates to be involved into multidisciplinary fields.

The Wound Management Innovation CRC project

The Wound Management Innovation CRC addresses key challenges in improving wound healing to provide quality-of-life for people with wounds, and cost-effective wound care that lessens the burden on the health system through its three Research Programs. The program associated with QFAB will address the molecular and biological mechanisms that underlie wound healing, leading to the identification of therapeutic targets and biomarkers for creating novel diagnostic and prognostic tools and therapeutic solutions. In particular, it relates to:

1) proteomic and metabolomic analyses of wound fluid from healing vs. non-healing wounds

2) microbial analysis of wound fluid from healing vs. non-healing wounds

3) SNP analysis of patients with recurring vs. non-recurring venous ulcers and from people who scar vs. people who do not scar from burns

4) improved in vitro and in vivo models for testing skin integrity, maintenance and repair.

This project will provide a unique opportunity to integrate and/or co-jointly analyze large data sets from various sources: proteomics, metabolomics, clinical measurements as well as Single Nucleotide Polymorphism (SNP). 

Context

This project will be hosted by the Queensland Facility for Advanced Bioinformatics, situated in the Institute for Molecular Biology, University of Queensland, Brisbane.

The Institute for Molecular Bioscience is a national research and development initiative at the University of Queensland. The IMB is staffed by a multidisciplinary team of approximately 380 research scientists and students working in research divisions encompassing genomics and bioinformatics, genetics and developmental biology, cell biology, structural biology, biochemistry and molecular design.

The Queensland Facility for Advanced Bioinformatics (QFAB) is a leading facility with the commitment to help life science researchers unlock the full value of their research data through the application of bioinformatics. It delivers advanced bioinformatics solutions to enable the global efforts of biotechnology, research biology, drug discovery and translational medicine. QFAB is a collaboration between the University of Queensland, Queensland University of Technology, Griffith University and Department of Employment, Economic Development and Innovation.

For information on QFAB activities please refer to http://www.qfab.org. Details of the research interests of the Institute may be accessed on the Institute’s web site at http://www.imb.uq.edu.au

The projects will be coordinated by Dr Kim-Anh Le Cao, QFAB and Dr Kathy Ruggiero, University of Auckland - New Zealand.

Required Skills

In order to register for a PhD, the applicant should have a Master degree or equivalent. The applicant should have a strong background in statistics and computing. He/she should be familiar with Linux (or Unix) and R. Good written English and communication skills are essential.