About This Opportunity

The School of Psychology and the National Centre for Youth Substance Use Research (NCYSUR) are seeking a Senior Data Scientist to play a pivotal role in advancing innovative, evidence-based research addressing alcohol and other drug use and mental health outcomes. Working within a highly collaborative, interdisciplinary research environment, this role will lead the development of robust data systems and advanced analytics that translate complex health data into meaningful insights, decision support tools and real-world impact across multiple nationally funded research programs.

Key responsibilities will include:

• Providing specialist expertise in data science methodologies, including machine learning and artificial intelligence, across the full research lifecycle.

• Designing and implementing efficient systems for data collection, cleaning, integration and governance to support large-scale clinical and implementation research.

• Leading the development of dashboards and decision support tools that enhance research translation and public health outcomes.

• Collaborating with multidisciplinary research teams and stakeholders to deliver high-quality, innovative research outputs and reports.

• Contributing to research quality assurance, continuous improvement activities and technical leadership initiatives.

• Training and supporting researchers and end users in the effective use of data systems, dashboards and analytical tools.

• Exercising supervisor-level leadership and people management responsibilities in line with the UQ Leadership Framework.

This is a full-time, fixed-term position for up to 3 years at HEW Level 8.

About You

You will bring a strong blend of technical expertise, research insight and collaborative capability, including:

• A PhD in data science, machine learning, artificial intelligence or a related discipline; or postgraduate qualifications with subsequent relevant experience.

• Demonstrated expertise in data science and machine learning, focusing on health-related applications.

• High-level proficiency in machine learning, AI techniques (deep learning, random forests, etc.), and languages such as R, Python, or Julia for health data analysis.

• Experience in backend/frontend development, data visualisation, and web apps using JavaScript, Python, and Linux.

• Strong interpersonal and communication skills with proven ability to produce clear, succinct research documentation and liaise effectively with a wide range of researchers and stakeholders.

• A demonstrated commitment to research integrity, ethics, workplace health and safety, and the University’s values of respect, openness and integrity.

• Proven ability to work collaboratively within interdisciplinary teams and contribute to a positive, inclusive research culture.

Interested?

For more information about this opportunity, please contact Professor Leanne Hides at l.hides@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 and cover letter summarising how your background aligns to the ‘About You’ section.

Other Information

Pre-employment checks may include verification of the right to work in Australia (employer-sponsored work rights are not available for this appointment), qualifications, criminal history checks, and other checks relating to integrity and conduct requirements.

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 criterion 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 Wednesday 6 May 2026 at 11.00pm AEST (Job Reference Number R-64272).