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Postdoctoral Research Fellow - Data… at University of… · Dutton…
Job Description
Postdoctoral Research Fellow - Data Science
Location: Dutton Park
Full-time, fixed-term position until December 2028
Base salary will be in the range $85,372 - $113,659 + 17% super (Academic Level A)
Based at our Dutton Park Campus
About This Opportunity
Join a visionary and collaborative research team driving world-leading advances in melanoma and skin cancer research. Working at the intersection of data science, artificial intelligence, medical imaging, and clinical research, you will play a pivotal role in transforming complex research data into meaningful discoveries that have the potential to improve health outcomes globally.
As a highly skilled Data Scientist, you will work alongside leading researchers, clinicians, AI specialists, and technical experts, leveraging cutting-edge technologies and world-class research infrastructure to develop innovative analytical solutions, enhance research capability, and help create lasting impact through data-driven discovery.
At UQ, you will be challenged, inspired and rewarded while contributing to research that is part of something bigger, creating change together.
Key responsibilities will include:
Research: Design, develop and optimise clinical and skin imaging data management systems, workflows and research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to innovative melanoma and skin cancer research outcomes.
Research Data Management and Analysis: Lead the processing, cleaning, integration, validation and analysis of complex clinical and skin imaging datasets, including 2D and 3D medical imaging data. Develop, maintain and deploy robust, version-controlled analytical codebases and data solutions that support high-quality, reproducible research.
Collaboration and Stakeholder Engagement: Collaborate with researchers, clinicians, AI specialists and technical experts to enhance data platforms, modelling capability and analytical approaches. Provide specialist technical expertise, contribute to multidisciplinary research projects, and support continuous improvement across research systems and processes.
Supervision and Researcher Development: Train, mentor and support junior staff in data cleaning, quality assurance, data management and analytical best practices. Foster capability development and contribute to a collaborative and high-performing research environment.
This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance.
About You
Completion of a PhD in Data Science, Biostatistics, Computer Science, Health Informatics, or a closely related discipline.
Demonstrated experience working with large, complex and longitudinal research datasets, including data cleaning, preprocessing, integration and quality assurance to support high-quality research outcomes.
Proven expertise developing, validating and deploying advanced statistical and machine learning models using Python, R, or similar programming languages in a research environment.
Experience working with melanoma, skin cancer or medical imaging research, including the analysis and management of 2D and 3D imaging datasets.
Strong technical knowledge across the data lifecycle, including research data architecture, data pipelines, database management, SQL, REDCap, cloud or high-performance computing environments, and reproducible research practices.
Excellent communication, stakeholder engagement and collaboration skills, with the ability to work effectively across multidisciplinary teams and provide training, mentoring and technical guidance to researchers and staff.
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. 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, access to exclusive internal-only vacancies, and genuine career progression opportunities via the academic promotions process.
Interested?
For more information about this opportunity, please contact Caitlin Horsham at c.horsham@uq.edu.au
For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au, stating the job reference number (below) in the subject line.
When you apply, please ensure you upload a resume, cover letter, and responses to the ‘About You’ section.
Other Information
Pre-employment checks may include verification of the right to work in Australia, qualifications, criminal history checks and mandatory immunisations. This may also include checks relating to gender-based violence matters or other integrity and conduct requirements.
Relocating from interstate or overseas? We may support you with obtaining employer-sponsored work rights and a relocation support package, however upfront costs will still be expected to be covered. You can find out more about life in Australia’s Sunshine State here.
We're dedicated to equity, diversity, and inclusion. We recognise that career pathways and opportunities differ and encourage applications from candidates who may not meet every criteria but can demonstrate their potential relative to opportunity. We’re also happy to support any accessibility needs throughout the recruitment process. Just let us know how we can help by emailing talent@uq.edu.au or calling +61 7 3365 2623.
Applications close 14th of October 2026 at 11.00pm AEST (R-68823). Please note that interviews have been tentatively scheduled for late October 2026.