Postdoctoral Research Fellow – ARC Training Centre for Information Resilience

• Electrical Engineering and Computer Science   

• Join a university ranked in the world’s top 50  

• Collaborate with highly awarded, world-class colleagues 

• Strong commitment and action toward a diverse and inclusive workforce 

• Based at our vibrant and picturesque St Lucia Campus  

About UQ 

As part of the UQ community, you’ll 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. 

About This Opportunity  

This is an exciting opportunity for a Postdoctoral Research Fellow to contribute to innovative research developments within the scope of data management and data mining. This position will be jointly supported by ARC Discovery Project DP200103650 Making Spatiotemporal Data More Useful: An Entity Linking Approach and the Australian Research Council (ARC) Industrial Transformation Training Centre for Information Resilience (CIRES). 

This position will be based in CIRES which provides additional opportunities to the successful candidate to work across multiple projects with industry and government partners, providing a wealth of experience in multi-disciplinary teams, research planning, and industry and public sector dynamics. As a research focused academic at level A the incumbent will be supported and guided by more senior academic research staff with the expectation of an increasing degree of autonomy over time. 

Key responsibilities will include:  

Research 

• Conduct innovative and reproducible research related to data management, with a particular focus on entity linking and privacy protection of spatiotemporal data.  

• Disseminate results through high-quality publications and open-source algorithms.  

• Participate in regular meetings to discuss project objectives, methodology and outcomes.  

• Participate in interactions and liaisons with research and industry collaborators.  

• Produces quality research outputs consistent with discipline norms by publishing or exhibiting in high-quality outlets. 

• Participate in applications for competitive research funding to support projects and activities. 

• Work with colleagues in the development of joint research projects and applications for competitive research funding support. 

• Contribute to progressing towards transfer of knowledge, technology and practices to research end users through translation, including commercialisation of UQ intellectual property. 

• Develop a coherent research program and an emerging research profile. 

• Review and draw upon best practice research methodologies. 

Supervision and Researcher Development 

• Contribute to the effective supervision of Honours and Higher Degree by Research students (as appropriate). 

• Demonstrate personal effectiveness in supervision and the management of researcher development. 

• Effectively lead and develop supervisee performance and conduct by providing feedback, coaching, and professional development. 

• As appropriate, manage research support staff effectively throughout the employee lifecycle in accordance with University policy and procedures. 

• Work to promptly resolve conflict and grievances when they arise in accordance with University policy and procedures. 

Citizenship and Service 

• Show leadership of self through collaboration and active participation in priority activities for the unit 

• Provide support to other academic positions and unit operations as needed during other team members’ absences. 

• Contribute to internal service roles and administrative processes as required, including participation in decision-making and service on relevant committees. 

• Collaborate in service activities external to the immediate organisation unit. 

• Begin to develop external links and partnerships by cultivating relationships with industry, government departments, professional bodies and the wider community. 

• Any other duties as reasonably directed by the supervisor. 

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

This is a full-time fixed-term position from 15th February 2024 – 14th February 2026 at Academic level A. The full-time equivalent base salary will be in the range $75,808.68 - $100,926.59 plus a generous super allowance of up to 17%. The total FTE package will be up to $88,696.16 - $118,084.11 annually. As this role is covered by an Enterprise Agreement, you will also receive regular remuneration increases – at least once a year. 

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   

• Completion or near completion of a PhD in Computer Science in the area of Data Management, Data Mining, or Data Science, preferably with experience in multi-modality data including but not limited to spatiotemporal data.  

• Demonstrated expert knowledge and experience in developing machine learning and deep learning methods, preferably pre-training and self-supervised learning techniques applied to spatiotemporal data analysis 

• Knowledge of issues and challenges underpinning modern data science, especially spatiotemporal data management (e.g., data storage, data integration, spatiotemporal indexing, data mining,). 

• Experience in conducting research projects, demonstrating high-level written and oral communication skills.  

• Peer-reviewed publications in high-impact journals or premiere conferences relevant to data mining or data science, e.g., SIGMOD, VLDB, ICDE, KDD, ICDM, AAAI, IJCAI, WWW, SIGIR, CIKM, CVPR, ICML, NeurIPS and ACM/IEEE transactions.  

• Ability to work both independently and as a member of a cross-disciplinary research team.  

• Experience in supervising research students (e.g., PhD, Mphil, Honours).  

Desirable  

• Demonstrated experience in working on long-term (at least one year) research projects.  

• Ability to develop industry liaisons and professional contacts  

• Broad knowledge of industry solutions and tools in data science 

In addition, the following mandatory requirements apply: 

• Work Rights:  Visa sponsorship may be available for this appointment.  

• Background Checks: All final applicants for this position may be asked to consent to a criminal record check. Please note that people with criminal records are not automatically barred from applying for this position. Each application will be considered on its merits.  

Relocating from interstate or overseas? You can find out more about life in Australia’s Sunshine State here . 

 
Questions?  

For more information about this opportunity, please contact Professor Shazia Sadiq at [email protected]  

 For application queries, please contact [email protected] 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  

At UQ we know that our greatest strengths come from our diverse mix of colleagues, this is reflected in our ongoing commitment to creating an environment focused on equity, diversity and inclusion .  We ensure that we are always attracting, retaining and promoting colleagues who are representative of the diversity in the broader community, whether that be gender identity , LGBTQIA+ , cultural and/or linguistic , Aboriginal and/or Torres Strait Islander peoples , or people with a disability . Accessibility requirements and/or adjustments can be directed to [email protected]    

If you are a current employee (including casual staff and HDR scholars) or hold an unpaid/affiliate appointment, please login to your staff Workday account and visit the internal careers board to apply for this opportunity. Please do NOT apply via the external job board. 

Applications close Tuesday 9th Jan 2024 at 11.00pm AEST (R-33613).