About This Opportunity We are seeking a highly motivated Postdoctoral Research Fellow to join an innovative research project focused on developing Australia's first trustworthy information recommender system. This groundbreaking work addresses the critical need for reliable and ethical online media platforms within a multicultural context. This position is based at the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ) and includes collaboration with MostWA, a leading Australian online media platform. As a Level A research-focused academic, the successful candidate will receive guidance and support from senior academic research staff, with opportunities to take on increasing levels of autonomy as they progress. The role involves working closely with Professor Hongzhi Yin, a distinguished academic in Data Science at EECS, to advance the project's objectives and contribute to impactful outcomes in trustworthy data mining and recommendation systems. Key responsibilities will include: Research: Establish a research program, collaborate on research projects, seek and manage research funding, publish in reputable journals, utilize best practice research methodologies, and participate in project discussions. Supervision and Researcher Development: Supervise students, recruit and manage employees, provide performance feedback and training, resolve conflicts, and ensure correct remuneration and benefits. 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, and genuine career progression opportunities via the academic promotions process. About You Completion or near completion of a PhD in Computer Science, Data Science, or a related field, with a strong focus on recommendation systems, trustworthy data mining, and AI. Demonstrated expertise in developing and applying advanced data mining and deep learning techniques, preferably in privacy-preserving data mining, trustworthy recommender systems, and large language models for recommendation. Demonstrated expertise in developing efficient models for very large-scale data processing in environments with limited computing resources. Strong programming skills in Python and familiarity with deep learning frameworks such as TensorFlow or PyTorch. 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 and data science, e.g., SIGIR, KDD, ICDE, VLDB, TheWebConf, WSDM, CIKM, ICDM, and ACM/IEEE transactions. Ability to work both independently and as a member of a cross-disciplinary research team. Desirable Demonstrated experience in working on long-term (three years) research projects. Ability to develop industry liaisons and professional contacts. Experience in collaborating with online media managers and an understanding of the challenges associated with developing production-level trustworthy information recommendation platforms. Broad knowledge of industry solutions and tools in data science. Experience in supervising research students (e.g., PhD, MPhil, Honours). The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, criminal check, education check, etc. 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 Professor Hongzhi Yin (h.yin1@uq.edu.au). For application queries, please contact 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 2 April 2025 at 11.00pm AEST (R-46519). Please note that interviews have been tentatively scheduled for late April 2025. If you apply for this position please say you saw it on Computeroxy

About This Opportunity

We are seeking a highly motivated Postdoctoral Research Fellow to join an innovative research project focused on developing Australia's first trustworthy information recommender system. This groundbreaking work addresses the critical need for reliable and ethical online media platforms within a multicultural context. This position is based at the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ) and includes collaboration with MostWA, a leading Australian online media platform. As a Level A research-focused academic, the successful candidate will receive guidance and support from senior academic research staff, with opportunities to take on increasing levels of autonomy as they progress. The role involves working closely with Professor Hongzhi Yin, a distinguished academic in Data Science at EECS, to advance the project's objectives and contribute to impactful outcomes in trustworthy data mining and recommendation systems.

Key responsibilities will include:

Research: Establish a research program, collaborate on research projects, seek and manage research funding, publish in reputable journals, utilize best practice research methodologies, and participate in project discussions.
Supervision and Researcher Development: Supervise students, recruit and manage employees, provide performance feedback and training, resolve conflicts, and ensure correct remuneration and benefits.
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, and genuine career progression opportunities via the academic promotions process.

About You

Completion or near completion of a PhD in Computer Science, Data Science, or a related field, with a strong focus on recommendation systems, trustworthy data mining, and AI.
Demonstrated expertise in developing and applying advanced data mining and deep learning techniques, preferably in privacy-preserving data mining, trustworthy recommender systems, and large language models for recommendation.
Demonstrated expertise in developing efficient models for very large-scale data processing in environments with limited computing resources.
Strong programming skills in Python and familiarity with deep learning frameworks such as TensorFlow or PyTorch.
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 and data science, e.g., SIGIR, KDD, ICDE, VLDB, TheWebConf, WSDM, CIKM, ICDM, and ACM/IEEE transactions.
Ability to work both independently and as a member of a cross-disciplinary research team.

Desirable

Demonstrated experience in working on long-term (three years) research projects.
Ability to develop industry liaisons and professional contacts.
Experience in collaborating with online media managers and an understanding of the challenges associated with developing production-level trustworthy information recommendation platforms.
Broad knowledge of industry solutions and tools in data science.
Experience in supervising research students (e.g., PhD, MPhil, Honours).

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

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 Professor Hongzhi Yin (h.yin1@uq.edu.au). For application queries, please contact 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 2 April 2025 at 11.00pm AEST (R-46519). Please note that interviews have been tentatively scheduled for late April 2025.

If you apply for this position please say you saw it on Computeroxy

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