The Borevitz laboratory (http://biology.anu.edu.au/Justin_Borevitz) within the Research School of Biology will develop and apply next-generation bioinformatics methods for genotyping by sequencing in plant models, crops and foundation species to be utilized in Landscape Genomics and Genome Wide Association Studies.
Term of Contract
Fixed Term of 36 Months
$80,166 - $91,299 pa plus 17% superannuation
View Academic Salary Information...
15 May 2012
Plant adaptation to climate change requires an understanding of the functional genetic diversity required to survive and thrive across varying environmental conditions. Methods to partition this diversity from background population structure are becoming available, aided by advances in genome sequencing. The Research Fellow will develop and apply methods to profile individual, family and population level genomic diversity and partition adaptive generic variation from the demographic background signature. The Research Fellow will work on bioinformatics projects that include the development of methods for the analysis of next-generation sequencing data, including RNA sequencing and/or genotyping-by-sequencing data, with applications in population, landscape, and quantitative genetics. The Research Fellow will have a firm background in computer science or bioinformatics, solid experience in the analysis of either genomic, transcriptomic or population genetics data and a PhD in a similar field. Enquiries contact officer: Associate Professor Justin Borevitz Email: firstname.lastname@example.org Telephone: +61 2 6125 3068
PURPOSE STATEMENT: A Level B Academic (Research Intensive) is expected to carry out independent and/or team research within the field in which he/she is appointed and to carry out activities to develop his/her research expertise relevant to the particular field of research. The Research Fellow leads the Landscape and Quantitative Genomics research areas in the laboratory of Associate Professor Justin Borevitz. The Research Fellow is also responsible for providing guidance to technicians and students in the implementation of the research work. KEY ACCOUNTABILITY AREAS: Development of Genotyping by Sequencing approaches for hapmap imputation, to be used in Landscape Genomic and Genome Wide Association Studies. This is applied in plant model organisms, crops and/or foundation species. Position Dimensions and Relationships: Development of Genotyping by Sequencing approaches for hapmap imputation, to be used in Landscape Genomic and Genome Wide Association Studies. This is applied in plant model organisms, crops and/or foundation species. Role Statement: Under broad direction the Research Fellow will: - develop and apply next-generation bioinformatics methods for genotyping by sequencing - perform hapmap imputation from Genotyping by Sequencing data - perform Genome Wide Association Studies and undertake clinical analysis - author and contribute to publications and conference presentations - provide guidance to technicians, students and junior members of research-only academic staff in his/her research area; - attendance at meetings associated with research or the work of the organisational unit to which the research is connected and/or departmental and/or faculty meetings and/or membership of a limited number of committees - Take reasonable care for your own workplace health and safety and not willfully place at risk the health or safety of any other person in the workplace. - other duties as allocated by the supervisor or the Vice-Chancellor consistent with the classification of the position. Skill Base A Level B Academic will normally have completed a relevant doctoral qualification or have equivalent qualifications or research experience. In addition he/she may be expected to have had post-doctoral research experience that has resulted in publications, conference papers, reports or professional or technical contributions that give evidence of research ability.
1. A PhD with proven research capability in computational molecular biology 2. Demonstrated experience in the analysis of either genomic, transcriptomic or population genetics data 3. Demonstrated experience in computer science and/or bioinformatics, including a demonstrated ability to write computer applications/analyses pipelines for analysis of biological data. 4. Proven experience in Unix/Linux operating systems and programming. 5. Demonstrated knowledge of and experience in statistical analysis of the mechanisms of gene expression at the RNA level. 6. Strong oral and written communication skills with demonstrated capacity to publish research findings 7. A demonstrated understanding of equal opportunity principles and policies and a commitment to their application in a university context.