Lecturer in Machine Learning and Computer Vision

School of Electrical Engineering and Computer Science (EECS) – Faculty of Engineering

Full-time (100%), Permanent Position

Base salary will be in the range $114,824.05 - $136,048.72 + 17% Superannuation (Academic Level B)

Visa sponsorship is not available for this position

Based at our St Lucia Campus - Brisbane

About This Opportunity

The School of Electrical Engineering & Computer Science (EECS) is seeking a talented academic to join as a Lecturer in Machine learning and Computer Vision.

We are looking for a teaching and research academic with a strong expertise in applied AI and current industry trends. Join us and help shape the future of AI and multimedia in a dynamic, collaborative environment.

Key Responsibilities Will Include:

• Teaching: Coordinating and delivering undergraduate and postgraduate courses, including lectures, tutorials, assessment, and marking. It includes developing engaging and up-to-date course materials in consultation with program advisors and stakeholders. The position supports innovation in curriculum design, such as online learning and short-form credentials, while ensuring course quality aligns with industry and academic standards. Responsibilities also include research training and supervision of higher degree research students, providing academic support and counselling to students, and assisting colleagues as needed.
• Research: Leading and contributing to independent and collaborative research programs with the goal of achieving national and international recognition. It includes securing and managing competitive external research funding, publishing in high-quality academic and professional journals, and developing interdisciplinary research projects in alignment with the School’s strategic priorities.
• Supervision and Researcher Development: Supervise students, recruit and manage employees, provide performance feedback and training, manage staff across the employee lifecycle and resolve conflicts.
• 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 teaching and research 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

Essential

• A PhD in Computer Science or a related field.
• Demonstrated record of research in multimedia computing and computer vision, with evidence of research standing at the early-career stage.
• A solid track record of publications in reputable refereed journals and conferences.
• Strong evidence of contribution to research, including successful grant applications.
• Demonstrated contribution to teaching at undergraduate, honours, and postgraduate levels.
• High level of effective communication and interpersonal skills.

Desirable

• Knowledge of state-of-the-art technologies and industry trends in focus areas – digital agriculture and digital manufacturing.
• Demonstrated capacity to utilise cutting-edge AI/ML technologies to address national challenges through real-world applications, particularly in digital agriculture and digital manufacturing.
• Established industry liaisons and professional contacts.
• Demonstrated contribution to research collaborations with other disciplines and/or industry partners.
• Proven ability to successfully lead a research team.

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. 

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 Helen Huang via helen.huang@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:

• Resume

• Cover Letter

• Responses to the ‘About You’ section

Our strength as an institution lies in our diverse colleagues. We are dedicated to equity, diversity, and inclusion, fostering an environment that mirrors our wider community. We are 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 do not 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 on Friday 10 October at 11.00pm AEST (R-56167).