• 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

• Resolving genetic mechanisms of complex human disease by applying single-cell and statistical genetics methods.
• Leading aspects of the project
• Staying informed on advances in computational methods genomics, 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

• A Ph D in a relevant field such as bioinformatics, computer science, biology, statistics or other relevant areas.
• High proficiency in programming and scripting languages (e.g. Python, R).
• Experience with Unix and HPC environments
• Experience in managing large datasets in an HPC environment
• 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.

• Proficiency with C/C++, Java and/or Perl scripting languages
• Experience and expertise in ML/AI algorithms for analysis of genomic data.
• 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).