Join a team committed to advancing cancer research at UQ, where your expertise in bioinformatics will help drive discoveries that make a real difference. As the Bioinformatician/Genomics Research Data Analyst, you will play a key role in a dynamic cancer genomics research program, providing high-level specialist support across a diverse portfolio of projects. You will analyse and interpret genomic, transcriptomic, epigenomic and spatial transcriptomic data across multiple cancer types, generating insights that propel our scientific aims and contribute to UQ’s mission to create transformative, research-driven impact.
Key responsibilities will include:
Provide expert bioinformatic support for cancer genomics research, including analysis of in-house and public omics datasets and presentation of findings to collaborators.
Develop and implement advanced analysis tools using R and Python, contributing to coordinated research outputs, reports, and manuscripts.
Conduct literature reviews, analyse preliminary data for grant applications, and support research quality assurance and continuous improvement activities.
Mentor and train students and junior research scientists, fostering skill development within a collaborative research environment.
This is a part-time (80%), fixed-term position through to 31st December 2027 at HEW Level 7.
We are looking for an experienced and highly motivated Bioinformatician with experience in Omics data analysis to support cancer research involving different Omics technologies to gain insights into tumour biology and identify potential treatment avenues. The successful candidate will have significant experience and expertise in analysing, visualising and combining various datasets, to extract deeper understanding of the data and answer questions relevant for our projects. You will have the opportunity to learn how to analyse data sets of new technologies to further enhance the understanding of cancer biology.
Postgraduate qualification or Master’s in bioinformatics, with experience in cancer omics data, or equivalent combination of education and experience.
Strong expertise in bioinformatics and omics datasets, including genomic, transcriptomic, epigenetic, and spatial technologies.
Advanced proficiency in R, Python, and Unix/Linux environments, with demonstrated ability to apply these to complex data analyses.
Experience in multidisciplinary research environments, including co-supervision and training of students and junior staff.
Proven track record in preparing manuscripts for peer-reviewed journals and producing clear, effective research documentation.
Commitment to UQ values, research integrity, ethics, and workplace health and safety, coupled with strong interpersonal and communication skills.
You must maintain unrestricted work rights in Australia for the duration of this appointment to apply. Employer sponsored work rights are not available for this appointment.
For more information about this opportunity, please contact Dr Katia Nones k.nones@uq.edu.au
For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au, stating the job requisition ID in the subject line.
We welcome applications from all individuals and are committed to an inclusive and accessible recruitment process. To be considered, please ensure you upload:
Resume
A cover letter summarising how your background aligns with the 'About You' section
Our strength as an institution lies in our diverse colleagues. We're dedicated to equity, diversity, and inclusion, fostering an environment that mirrors our wider community. We're committed to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact talent@uq.edu.au.
UQ is committed to a fair, equitable and inclusive selection process, which recognises that some applicants may face additional barriers and challenges which have impacted and/or continue to impact their career trajectory. Candidates who don’t meet all criteria are encouraged to apply and demonstrate their potential. The selection panel considers both potential and performance relative to opportunities when assessing suitability for the role.
Applications close Tuesday 25th November 2025 at 11.00pm AEST (R-57575). Please note that interviews have been tentatively scheduled for week commencing 1st December.