Role type: Full Time, Fixed Term for 2 years
Faculty: Faculty of Science
School: School of Mathematics and Statistics
Salary: Level A.4 - $102,218 p.a. plus 17% super
Faculty: Faculty of Science
School: School of Mathematics and Statistics
Salary: Level A.4 - $102,218 p.a. plus 17% super
- Analyse diverse omics datasets, contribute to pioneering research and develop integrative bioinformatics skills
- Apply now to join a world-class team advancing the frontiers of multi-omics integration and analysis
- Investing in you - benefits package including salary packaging, health and wellbeing programs, discounted services, and professional development opportunities.
The University of Melbourne
We take pride in our people, who all contribute to our mission to benefit society through the transformative impact of education and research. Discover more via our website.
We take pride in our people, who all contribute to our mission to benefit society through the transformative impact of education and research. Discover more via our website.
Your next career opportunity
As a Data Analyst in the Lê Cao lab, you'll play a crucial role in unravelling complex biological systems through integrative analysis of high-throughput omics datasets. You'll have the opportunity to work on diverse projects, from transcriptomics to single-cell analysis, contributing to cutting-edge research in molecular biology. Working within a multidisciplinary team, you'll develop and implement reproducible analysis pipelines, collaborate on high-impact publications, and potentially contribute to the renowned mixOmics toolkit.
As a Data Analyst in the Lê Cao lab, you'll play a crucial role in unravelling complex biological systems through integrative analysis of high-throughput omics datasets. You'll have the opportunity to work on diverse projects, from transcriptomics to single-cell analysis, contributing to cutting-edge research in molecular biology. Working within a multidisciplinary team, you'll develop and implement reproducible analysis pipelines, collaborate on high-impact publications, and potentially contribute to the renowned mixOmics toolkit.
Your responsibilities will include:
- Omics Data Analysis: Conduct end-to-end analytics across diverse omics data types, including quality control, statistical modelling, and multi-omics integration.
- Reproducible Research: Develop and maintain well-documented, version-controlled analysis workflows in R and Python.
- Collaborative Projects: Work closely with lab members and external collaborators, translating scientific questions into analytical plans and delivering interpretable results.
- Knowledge Dissemination: Contribute to publications, present findings, and support mixOmics-related training activities.
You may be a great fit if:
You are a detail-oriented and proactive data analyst with a strong background in bioinformatics or computational biology, demonstrating expertise in statistical programming and a passion for solving complex biological problems through data-driven approaches.
You are a detail-oriented and proactive data analyst with a strong background in bioinformatics or computational biology, demonstrating expertise in statistical programming and a passion for solving complex biological problems through data-driven approaches.
You may also:
- Hold a Masters degree in Bioinformatics, Computational Biology, Statistics, or a closely related discipline.
- Have experience in analysing high-throughput omics data across various types (e.g., transcriptomics, proteomics, metabolomics).
- Demonstrate strong statistical and computer programming skills in R and Python.
- Possess an active GitHub profile showcasing ongoing code development and contributions.
What we offer you
We offer the opportunity to be part of a vibrant community and enjoy a comprehensive range of benefits to support your success and sense of fulfilment, including:
We offer the opportunity to be part of a vibrant community and enjoy a comprehensive range of benefits to support your success and sense of fulfilment, including:
- Supportive flexible work arrangements underpinned by our commitment to inclusion and well-being
- Progressive, considerate leave provisions to empower your work-life balance
- Salary packaging and access to a range of discounted services including Bupa health insurance
- Health and well-being services including a leading Employee Assistance Program
Your new team – Lê Cao lab, Melbourne Integrative Genomics (MIG)
https://sites.research.unimelb.edu.au/integrative-genomics | https://lecao-lab.science.unimelb.edu.au
Lê Cao lab is part of Melbourne Integrative Genomics (MIG), which has been established in 2017 and is an initiative to strengthen the involvement of statisticians in the advances being made in genomics and computational biology. MIG is an interdisciplinary research centre for the application of maths/stats/computing techniques to omics profiling data to help understand genotype-to-phenotype process in humans and other organisms. MIG includes 50+ members, and provides a wide range of opportunities for exciting research collaborations. The Parkville precinct has the greatest concentration of biological and medical research in Australia, and is among the greatest internationally.
http://www.ms.unimelb.edu.au
The University of Melbourne's School of Mathematics and Statistics is one of Australia's leading mathematics and statistics schools. It has achieved this status through the high quality of its research and teaching programs. The School offers a wide range of subjects to undergraduate and postgraduate students and is involved in aspects of community life that impact on the interests of the School and the discipline.
https://sites.research.unimelb.edu.au/integrative-genomics | https://lecao-lab.science.unimelb.edu.au
Lê Cao lab is part of Melbourne Integrative Genomics (MIG), which has been established in 2017 and is an initiative to strengthen the involvement of statisticians in the advances being made in genomics and computational biology. MIG is an interdisciplinary research centre for the application of maths/stats/computing techniques to omics profiling data to help understand genotype-to-phenotype process in humans and other organisms. MIG includes 50+ members, and provides a wide range of opportunities for exciting research collaborations. The Parkville precinct has the greatest concentration of biological and medical research in Australia, and is among the greatest internationally.
http://www.ms.unimelb.edu.au
The University of Melbourne's School of Mathematics and Statistics is one of Australia's leading mathematics and statistics schools. It has achieved this status through the high quality of its research and teaching programs. The School offers a wide range of subjects to undergraduate and postgraduate students and is involved in aspects of community life that impact on the interests of the School and the discipline.
Please note: This role requires current valid work rights for Australia. Visa sponsorship is not available.
A Working with Children Check (WWCC) is required for all positions. If successful, we'll guide you through the WWCC application process during onboarding and reimburse the cost.
A Working with Children Check (WWCC) is required for all positions. If successful, we'll guide you through the WWCC application process during onboarding and reimburse the cost.
Join Us and unlock your career potential
If this role is right for you, please apply with the following documents:
For recruitment queries, email Anna at hr-careers@unimelb.edu.au. Include the Position Number and Job Title in the subject line. Please do not send applications to this email address.
For job-specific queries, refer to the contact details in the Position Description.
Applications close: 6 April 2026. 11:55 PM; Melbourne time zone.
Position Description:
JR-009381 Data Analyst in Omics_PD.docx
JR-009381 Data Analyst in Omics_PD.pdf
If this role is right for you, please apply with the following documents:
- Resume
- Cover Letter outlining your interest and experience
- The responses against the following Selection Criteria
- Masters degree in Bioinformatics, Computational Biology, Statistics, or a closely related discipline (or equivalent professional experience in a relevant setting).
- Experience performing statistical analyses of high-throughput omics data (for example transcriptomics, microbiome, proteomics, metabolomics, single-cell), including appropriate preprocessing and quality control.
- Demonstrated statistical and computer programming experience in R and Python.
- Demonstrated experience in version control on Github and an active GitHub profile evidencing ongoing code development and/or contributions.
For recruitment queries, email Anna at hr-careers@unimelb.edu.au. Include the Position Number and Job Title in the subject line. Please do not send applications to this email address.
For job-specific queries, refer to the contact details in the Position Description.
Applications close: 6 April 2026. 11:55 PM; Melbourne time zone.
Position Description:
JR-009381 Data Analyst in Omics_PD.docx
JR-009381 Data Analyst in Omics_PD.pdf