School of Electrical Engineering and Computer Science
Full-time (100%), fixed-term position for up to 2 years
Base salary will be in the range $80,448.78 - $107,104.10 + 17% Superannuation (Academic Level A)
Based at our St Lucia Campus
This is an exciting opportunity for a Postdoctoral Research Fellow/Research Officer to contribute to cutting-edge advancements in manufacturing through developing robust models and innovative demonstrations. The research will involve creating effective modelling techniques on embedded devices for large- scale spatio-temporal data analytics, prediction, and process optimization, with applications extending to real-world scenarios in digital manufacturing and industrial systems.
This role will produce tangible research outputs, including demonstrable solutions and prototypes, facilitating cross-disciplinary collaboration and enabling more efficient, reliable, and impactful manufacturing processes.
Key responsibilities will include:
Teaching: Assist with delivery of courses, engage in curriculum design, supervise and assess research students (PhD, MPhil, Honors), provide academic counselling, and adhere to university teaching rules.
Research: Establish a research program in the field of manufacturing systems and process control, collaborate on research projects, prepare research publications and progress reports, investigate advanced data analysis for manufacturing systems, utilize best practice research methodologies, and participate in project discussions.
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 UQAs 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 YouA PhD (completed or near-completion) in computer science, engineering, or a related discipline (preferably in image processing, signal processing, or knowledge discovery).
Demonstrated track record in computer vision, image analysis, and data- driven system development.
Demonstrated experience in engineering and system integration.
Demonstrated expert knowledge and experience in developing advanced computational methods to address real-world challenges associated with complex, heterogeneous datasets in manufacturing or process optimization.
Experience in conducting cross-disciplinary or industrial research projects with tangible outcomes.
Evidence of publication of research findings in top international peer- reviewed journals/conferences relevant to the scope of the project, e.g., IEEE Transactions, ACM Transactions, or domain-specific venues for manufacturing and system engineering.
Excellent communication and interpersonal skills with the ability to work both independently in a research environment and as part of a cross- disciplinary team and to establish effective relationships with academic and industrial collaborators.
Advanced computer skills in developing algorithms, managing large-scale datasets, and showcasing research outcomes through prototypes or demonstrators.
High-level organization and time management skills, with demonstrated capacity to establish and achieve goals.
Desirable
Background in deep learning and computer vision.
Demonstrated experience in engineering and cross-disciplinary team working.
Experience in supervising research students and managing the work progress of participants in both academic and industrial projects.
The successful candidate may be required to complete a number of pre- employment checks, including: right to work in Australia, education check.
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 Helen Huang [email protected] and Dr Yadan Luo [email protected]. For application inquiries, please reach out to the Talent Acquisition team at [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
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 [email protected] for accessibility support or adjustments.
Applications close Sunday 23 February at 11.00pm AEST (R-47983).