Postdoctoral Research Fellow – ARC Training Centre for Information Resilience

• School of Information Technology and Electrical Engineering
• Academic Level A
• Fixed Term Position for up to 2 years
• Applications Close Monday 17th October 2022 at 11.00pm AEST (R-16572)

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 based in the Australian Research Council (ARC) Industrial Transformation Training Centre for Information Resilience (CIRES) working 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. The successful candidate will have the opportunity to work directly with the Centre’s partners, with an expected third of their time dedicated to working with partner organisations.

 Key responsibilities include:  
1. Research

• Conduct innovative and reproducible research related to information resilience, with a particular focus on dealing with data sparsity/noise problems in real-world datasets and promoting algorithmic transparency. 
• 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. 

2. Supervision and Researcher Development

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

3. Citizenship and Service

• Demonstrate citizenship behaviours that align to the UQ values.
• Shows 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. 

4. Other

Ensure you are aware of and comply with legislation and University policy relevant to the duties undertaken, including but not exclusive to:

• The University’s Code of Conduct .

• Requirements of the Queensland occupational health and safety (OH&S) legislation and related OH&S responsibilities and procedures developed by the University or Institute/School.

• The adoption of sustainable practices in all work activities and compliance with associated legislation and related University sustainability responsibilities and procedures .

• Requirements of the Education Services  for Overseas Students Act 2000, the National Code 2007 and associated legislation, and related responsibilities and procedures developed by the University.

  
About You

• Completion or near completion of a PhD in Computer Science (preferably in the area of Data Mining and Predictive Analytics). 

• Demonstrated expert knowledge and experience in developing machine learning and deep learning methods, preferably pre-training and self-supervised learning techniques for data mining and predictive analytics. 

• 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., KDD, ICDM, AAAI, IJCAI, WWW, SIGIR 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 

What We Can Offer  

 This is a Full-time, 100% FTE, Fixed-term position through to 31 October 2024 at Research Academic Level A. 

The full-time equivalent base salary will be in the range

$87,006.34 – $96,530.67 plus super of up to 17%. The total FTE package will be in the range $101,797.42- $112,940.88 per annum.  

The following flexible employment options may be available for this role: Some working from home; variable start or finish times; compressed hours.

For further information about UQ’s benefits, please visit Why Work at UQ  and review The University of Queensland’s Enterprise Bargaining Agreement 2018-2021 .  

 Questions?  

To discuss this role please contact Prof Shazia Sadiq on [email protected]

For application queries, please contact [email protected]  stating the job reference number in the subject line.  
 

 Want to Apply?  

All applicants must supply the following documents:  

• Cover letter addressing the About You section

• Resume  

Please note that you will be asked to add all documents into the one upload box labelled ‘resume’, which is step one of the application form.

To satisfy pre-requisite questions and ensure your application can be considered in full, all candidates must apply via the UQ Careers portal by the job closing deadline. Applications received via other channels, including direct email, will not be accepted.  

About The Selection Process  

As part of the Selection Process, applicants shortlisted for interview will be required to present a seminar and mock lecture to members of the school community prior to their scheduled interview. Research seminars and lecture topics will be provided with adequate notice to shortlisted candidates.  

The University of Queensland is committed to ensuring all candidates are provided with the opportunity to attend the panel interviews, however, for those candidates who are unable to attend in person, video interview options will be available.     

Other Information  

 Sponsorship: 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.   
 

We value diversity and inclusion, and actively encourage applications from those who bring diversity to the University. Our Diversity and Inclusion webpage  contains further information if you require additional support. Accessibility requirements and/or adjustments can be directed to [email protected] .

If you are a current employee of the University, or hold an unpaid or affiliate appointment with the University, 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.