• Generous salary packaging to save you income tax on your wages thereby boosting your monthly take home pay (max. $15,900 general expenses + $2,650 meals/accom)
• Ample opportunities for on-going training and development
• Stimulating, diverse and highly international research environment
• Flexible work arrangements e.g. start / finish times
• 18 weeks paid parental leave for both parents including paid superannuation
• A range of additional leave types to meet your personal needs including cultural leave, conference leave, community service and study leave
• Discounted Health Insurance
• Lifestyle discounts with our community partners

• Bioinformatics
  • Developing, running and maintaining single-cell analysis pipelines
  • Developing computational methods for statistical genetics and single-cell ‘omics research
• Computational biology
  • Resolving the genetic mechanisms of complex human disease by applying single-cell and statistical genetics methods.
  • Application of ML/AI algorithms and software to large-scale genomic data
  • Analysing data to answer research questions

• Staying informed on advances in computational genomics methods, as well as building and maintaining biological domain expertise
• Presenting results in internal meetings and conferences.
• Contributing to scientific manuscripts
• Collaborating with other group members and as part of national and international consortia
• Record-keeping and administrative aspects that underlie scientific research in discussion with group members and development of timelines.
• Attending, discussing and reviewing current and future techniques within the institute

• An honours degree or higher qualification in a relevant field such as bioinformatics, computer science, biology, statistics or other relevant areas, or an equivalent combination of relevant experience and/or education/training.
• High proficiency in Python and/or R
• Experience with Unix and HPC environments
• Demonstrated experience using version control for code development and curation
• An interest in genetics, and cellular biology
• Excellent problem-solving skills
• Good communication skills and strong in teamwork and collaborative research
• Excellent project management and organisation skills
• Ability to work independently and meet deadlines

• Experience in managing large datasets in an HPC environment
• High proficiency in programming and scripting languages (e.g. C/C++, Java, Perl, Python)
• Advanced user of the R programming language and R-based statistical packages and tools, such as those available from the Bioconductor project for high throughput genomic data analysis
• Good knowledge of statistics and presentation of molecular/clinical data.
• Experience in analysing and interpreting large genomic data sets (WGS, RNA-Seq, sc RNA-Seq)
• Experience and expertise in ML/AI algorithms for analysis of genomic data