Research Fellow - Data Science

• UQ Centre for Clinical Research

• Full-time, fixed-term position for 3 years with salary in the range $110,365.29 - $130,765.78 (Academic level B), plus a generous super allowance of up to 17%.

• A research support package of up to $50,000.

• Based at our Herston campus

Operational Research and Decision Support for Prevention, Control and Elimination of Infectious Diseases (ODeSI)

The ODeSI team has internationally recognised expertise in neglected tropical diseases, emerging infectious diseases, vaccine preventable diseases, and travel medicine. ODeSI’s mission is to optimise infectious disease prevention, control and elimination by generating new evidence, providing innovative solutions, and supporting clinical and public health decision making. The team has strong multidisciplinary partnerships with clinical and public health decision makers, and collaborate with them to co-design research, implement and evaluate interventions, and explore the application of innovative methods and new technologies for disease prevention and control.

ODeSI has extensive experience in operational research and field surveys (including international projects), predictive risk mapping and modelling (spatial epidemiology), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social
network analysis and dynamic data visualisation tools. Further information is available at https://clinical-research.centre.uq.edu.au/odesi 

About This Opportunity 

We are seeking a highly motivated Research Fellow to bring their expertise in Data Science and Machine Learning (ML)/Artificial Intelligence (AI) to the dynamic infectious diseases epidemiology team at the UQ Centre for Clinical Research. As part of the Health Research Accelerator (HERA), you will engage in cutting-edge research aimed at addressing some of the world’s most pressing health challenges, with a specific focus on infectious diseases and public health.

In this role, you will have the opportunity to further develop your expertise and enhance your research profile, with the goal of achieving national recognition in your field. As a Level B Research Fellow, you will be responsible for managing your own research program, contributing to service and engagement activities, and mentoring the next generation of researchers through effective student supervision.

This position presents a unique opportunity for an experienced data scientist to make a significant impact in the health research field, particularly within UQ’s ODeSI program. You will play a crucial role in designing and implementing decision support systems, leveraging state-of-the-art data science techniques, including machine learning and AI, to drive innovation and improve public health outcomes.

Key responsibilities will include: 

• Lead Research Initiatives: Drive research at the intersection of data science, epidemiology, and public health, focusing on the development of ML and AI models for disease prevention, control, and elimination.

• Collaborate on Interdisciplinary Research: Work with multidisciplinary teams to integrate innovative methods (e.g., spatial epidemiology, Bayesian networks) with machine learning techniques, driving cutting-edge research outputs.

• Research Output and Knowledge Translation: Publish high-quality research in peer-reviewed journals, present at conferences, and contribute to the transfer of knowledge and technology, including the commercialisation of UQ intellectual property.

• Supervision and Researcher Development: Supervise Honours and Higher Degree by Research students, provide mentorship in data science methodologies, and foster engagement in real-world projects.

• Citizenship and Service: Demonstrate leadership, actively participate in unit priorities, build partnerships, and manage internal service roles and administrative processes in alignment with UQ values.

This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance.

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, and genuine career progression opportunities via the academic promotions process.

About You 

• PhD in data science, machine learning, AI, or related field.

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

• Proficient in machine learning, AI techniques (deep learning, random forests, etc.), and languages like R, Python, or Julia for health data analysis.

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

• Track record of publications in peer-reviewed journals and conference presentations.

• Successful experience in obtaining and managing research funding.

• Proven ability to collaborate with external agencies on research initiatives.

• Experience in supervising and mentoring students in academic environments.

• Contributions to internal academic roles and participation in relevant external activities.

The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, education check and mandatory immunisations,

Relocating from interstate or overseas? We may support you with obtaining employer-sponsored work rights and a relocation support package. You can find out more about life in Australia’s Sunshine State here.

Questions? 

For more information about this opportunity, please contact Dr Luis Furuya Kanamori.  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.
 

Want to Apply? 

All applicants must upload the following documents in order for your application to be considered:

• Resume

• Cover letter

• Responses to the ‘About You’ section

Other Information 

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.

We know one of our strengths 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. Reach out to talent@uq.edu.au for accessibility support or adjustments.

Applications close Sunday 22nd June 2025 at 11.00pm AEST (R-50316). Please note that interviews have been tentatively scheduled for Thursday 17th July 2025.