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Research Associate in Statistical Methods for Livestock Genomics
The livestock industry is one of Australia's key industries, with local
and export markets measured in billions, and global recognition of
excellence. The increasing focus on the use of genomic data for improving
profitability, genetic gain and quality thus requires the development and
application of sound statistical methodology for experimental design, data
analysis and modelling. This represents exciting opportunities for
statistically trained researchers to adapt state-of-the-art methods and
develop new techniques to cater for the specialised needs of this
discipline.
A Research Associate is invited to be part of an ARC Linkage project on
the development and application of statistical methodology in livestock
genomics. The project is joint between Genetic Solutions Pty Ltd and the
University of Newcastle, Australia.
Genetic Solutions provides leading edge genetic information technology
for the livestock and aquaculture industries in Australia and globally.
Its products are based on a comprehensive intellectual property portfolio
of DNA and gene marker information. These products, which include
SureTRAK® and GeneSTAR®, are used by livestock production and processing
companies to improve product quality and production efficiency. Clients
include major pastoral companies, food processors and biotechnology
companies.
The Discipline of Statistics at the University of Newcastle is part of the
School of Mathematical Sciences in the Faculty of Science and Information
Technology at The University of Newcastle, Callaghan, Australia. Currently
the group comprises five full-time academic staff and a valued cohort of
research assistants, postgraduate research students and conjoints, with
focus on on-campus and distance teaching, statistical research and
statistical consulting.
Key research problems identified in the first instance include: (i)
analysis, modelling and testing for association between DNA pools with
extreme traits for fine mapping of economically important traits in
cattle; (ii) meta-analysis of existing genetic studies, accommodating
bias, measurement error and different types of data; (iii) methods for
comparative mapping and sequence analysis, and their application to
relevant data; (iv) Bayesian methods for mapping in gene discovery; (v)
experimental design to best exploit new and traditional types of data for
gene discovery.
The Chief Investigators in this project are Professor Kerrie Mengersen and
Dr Jay Hetzel. Dr Mengersen is Head of the discipline of Statistics at the
University of Newcastle. Her main interests are directly in line with this
project: Bayesian modelling, mixture models, MCMC algorithms and Bayesian
applications. Dr Hetzel is Scientific Director with Genetic Solutions. He
has built a distinguished international reputation in bovine genomics
during a 20 year research career in CSIRO, culminating in his election in
2001 as a Fellow of the Australian Academy of Technological Sciences and
Engineering.
The Research Associate will be based at Genetic Solutions
in Brisbane and will be expected to spend negotiated periods of time in
Newcastle.
Please email [log in to unmask] for further information or
discussion.
Applications close on the 30th August 2003. For application details about
the Research Associate position, please email
[log in to unmask] in the first instance.
Position Description: Research Associate
Position: Research Associate, three-year contract
Classification: Level 8, Step 2
Faculty/Division: Science and Information Technology
Dept/Branch/Unit: School of Mathematical and Physical Sciences
Immediate Supervisors: Professor Kerrie Mengersen and Dr Jay Hetzel
Overall Objective: Under general direction carry out research into new statistical
methods for livestock genomics
Duties: Without limiting the generality of the foregoing the Research
Associate will:
1. Liaise closely with the industry and academic partners in the project
2. Conduct relevant literature searches
3. Undertake research relevant to the project
4. Develop and apply new statistical methods to specific problems in livestock genomics
5. Develop computational algorithms and software to assist in the practical application of these approaches
6. Identify, collect and analyse relevant data as directed by the academic and industry investigators
7. Assist in the preparation of research papers and associated communications
8. Where appropriate, communicate results through oral presentations
9. Develop multi-disciplinary and multi-institutional networks in relevant areas
10. Be familiar with, and observe the University's policy and procedures on Equal Employment Opportunity and Occupational Health and Safety in the performance of the responsibilities of the position.
11. Undertake any other duties relevant and appropriate to this level.
Qualifications and/or Skills Required
· PhD in Statistics; or PhD in genetics, computing or biological sciences with strong statistics component
· Demonstrated knowledge of new statistical methods and ability to contribute to the development of these
· High level skills in computational statistics
· High level skills in statistical software and programming
· Experience in working in applied statistics
· Demonstrated research record evidenced through research publications, industry reports, conference presentations
· Ability to work both independently and as part of a team
· Good written and oral communication skills
· Ability to travel between Brisbane and Newcastle as required
Desirable Qualifications and/or Skills
· Interest in genomics, bioinformatics or related areas
· Interest in biometrics, in particular in livestock research
Place of Position with the Organisation
Professor
Research Associate
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