The University of Queensland – Saint Lucia QLD
Faculty of Humanities, Arts and Social Sciences (HASS)
Full-time (100% FTE), fixed term for two years from January 2026,
FTE base salary: $114,824.05 – $136,048.72 + 17% superannuation (Academic Level B).
Based at our St Lucia campus.
About This Opportunity
This is an exciting opportunity for a Research Data Scientist to contribute to the development of an enabling research capability for working with public interest data as part of the Reusable and Accessible Public Interest Documents (RAPID) project.
In this role, you will apply data science, software development, and research platform expertise to create tools, datasets, and workflows that support humanities and social sciences researchers across Australia. You will help build the technical foundations of the RAPID infrastructure while also engaging in mission‑led research to grow your own disciplinary profile in text data, analytics, and data‑centred research methodologies.
You will work collaboratively with project partners across UQ, QUT, QCIF, and the ARDC to deliver meaningful research infrastructure, training, and impact that extends beyond UQ's local research community.
This is a research focused position.
Further information can be found by viewing UQ's Criteria for Academic Performance.
Key Responsibilities
RAPID Project Delivery
* Develop software to collect, model, and prepare public interest datasets.
* Transform and integrate complex text data for qualitative and quantitative research use cases.
* Create exemplar tools, notebooks, and documented workflows for researchers.
* Deliver training on data use, analytics tools, and research workflows.
* Support researchers in applying RAPID data to their research questions.
* Identify new public interest data sources and opportunities for future project development.
* Implement improvements to data, documentation, and workflows based on researcher feedback.
* Prepare clear documentation, training materials, and guides for transparency and reuse.
Research & Engagement
* Produce high-quality publications and contribute to joint research outputs.
* Support collaborative research projects and funding applications.
* Build relationships with researchers, industry, and government stakeholders.
* Contribute to mentoring, collaboration, and team priorities.
Citizenship & Service
* Participate in service roles, committees, and community engagement activities.
* Support academic operations during staff absences.
Other
* Comply with University policies, including the Code of Conduct, WHS, sustainability, and ESOS obligations.
About RAPID
The Reusable and Accessible Public Interest Documents (RAPID) project sits within the Community Data Lab (CDL), a key focus area of the HASS & Indigenous Research Data Commons (HASS & IRDC). RAPID aims to:
* Deliver an accessible research platform for public interest documents such as Federal Hansard, inquiry submissions, and Ministerial records.
* Establish a metadata standard for Public Interest (PI) documents aligned with FAIR principles and government record keeping frameworks.
* Create documented workflows that support computational and qualitative research with PI documents.
About UQ
As part of the UQ community, you will have the opportunity to work alongside the brightest minds, who have joined us from all over the world, and within an environment where interdisciplinary collaborations are encouraged.
At the core of our teaching remains our students, and their experience with us sets a foundation for success far beyond graduation. UQ has made a commitment to making education opportunities available for all Queenslanders, regardless of personal, financial, or geographical barriers.
As part of our commitment to excellence in research and professional practice in academic contexts, we are proud to provide our staff with access to world‑class facilities and equipment, grant writing support, greater research funding opportunities, and other forms of staff support and development.
The greater benefits of joining the UQ community are broad: from being part of a Group of Eight university, to recognition of prior service with other Australian universities, up to 26 weeks of paid parental leave, 17.5% annual leave loading, flexible working arrangements including hybrid on site/WFH options and flexible start/finish times, access to exclusive internal‑only vacancies, and genuine career progression opportunities via the academic promotions process.
About You
* Completion of an honours or postgraduate degree in a relevant discipline with a research component, or equivalent research experience.
* Experience in one or more of: data analysis, data visualisation, statistics, text analytics, or machine learning.
* Experience modelling and transforming complex datasets from diverse sources.
* Demonstrated ability to write maintainable software for data analytics.
* A track record of contributing to research projects through to completion.
* Experience preparing documentation and training materials or delivering training for data‑intensive systems.
Questions?
For more information, please contact
* Dr Sam Hames: *******@uq.edu.au
* Professor Michael Haugh: *************@uq.edu.au
For application queries, please contact ******@uq.edu.au quoting the job reference number R-57752 .
Want to Apply?
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 1-page cover letter addressing the selection criteria.
Applications must be submitted via the UQ Careers portal by Monday 5 January 2026 at 11.00pm AEST. Interviews are tentatively scheduled on mid‑January 2026.
Other Information
UQ values diversity and inclusion and encourages applications from individuals who bring different perspectives to our community. Accessibility requirements and adjustments can be directed to ******@uq.edu.au
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