About This Opportunity
This is an exciting opportunity for a Postdoctoral Research Fellow/Research Officer to join our team exploring the intersection of data management and machine learning. Our research focuses on how core data systems can enhance AI, and how AI can improve the scalability and intelligence of data infrastructures.
We’re looking for a motivated researcher passionate about building intelligent systems that integrate machine learning, databases, and large language models. System building is a core research goal, not just a proof of concept.
The role will involve developing deployable prototypes, efficient big data algorithms, and publishing in top-tier venues in databases, machine learning, and data mining.
Key responsibilities will include:
Research:
Conduct original research at the intersection of databases and machine learning.
Develop learning-enhanced, target-oriented data ecosystems.
Improve AI systems using data management principles (e.g., quality, access, traceability).
Explore data-centric techniques to enhance AI model efficiency and deployment.
Build and evaluate system prototypes using real-world datasets.
Publish in top-tier venues and contribute to open-source tools and collaborations.
Prepare research outputs, including reports and publications.
Develop an independent program of research and an emerging profile in the field of data ecosystem.
Support proposal writing and engage with collaborators as needed.
Teaching and Learning:
Support senior staff in delivering high-quality teaching materials.
Assist with co-supervision of PhD, MPhil, and Honours students.
Participate in postgraduate recruitment events.
Guest lecture on advanced data science topics.
Service and Engagement:
Represent the team in industry and funding forums; build relevant networks.
Strengthen relationships with industry, government, and professional bodies.
Promote best practices in engineering, focusing on reproducibility and scalability.
Participate in research funding application and proposal writing.
Citizenship and Service: Develop partnerships, demonstrate leadership through mentoring, engage in internal service roles and committees, perform administrative functions, provide support to colleagues, and uphold university 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, access to exclusive internal-only vacancies, and genuine career progression opportunities via the academic promotions process.
About You
A PhD (completed or near-completion) in computer science, engineering, or a related discipline, with demonstrated research strength in data systems, AI for databases, or large-scale data infrastructure.
Deep expertise in core database system techniques, such as indexing, query processing, and system-level optimization.
Proven ability to conduct system-oriented research, with experience designing and evaluating complex data-intensive systems.
Strong programming (in C++, C, Java, and Python) and system design skills, with practical experience in large-scale data frameworks or database internals.
Evidence of publication of research findings in top international peer-reviewed journals/conferences relevant to the scope of the project, e.g. ACM SIGMOD, PVLDB, KDD.
Experience in conducting cross-disciplinary or industrial research projects with tangible outcomes.
Strong communication and interpersonal skills, with the ability to work independently and collaboratively within a high-performing, cross-disciplinary research team and engage effectively with academic and industry partners.
High-level organization and time management skills, with demonstrated capacity to establish and achieve goals.
The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, education check.
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.
Questions?
For more information about this opportunity, please contact Professor Zhifeng Bao zhifeng.bao@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.
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:
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.
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.
Applications close Wednesday 29 October at 11.00pm AEST (R-57319). Please note that interviews have been tentatively scheduled for the week commencing Monday 10 November.
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