Postdoctoral Research Fellow/Research Officer - Multi-Modal Imaging and 3D Analytics

• School of Electrical Engineering and Computer Science

• Full-time (100%), fixed-term position through to December 2027

• Base salary will be in the range $80,448.78 - $107,104.10 + 17% Superannuation (Academic Level A)

• Based at our St Lucia Campus

The Postdoctoral Research Fellow will be based in the School of Electrical Engineering and Computer Science, taking a leading role in advancing agricultural practices and sustainability. This will be achieved through cutting-edge multi-modal imaging (e.g., RGB, multispectral, hyperspectral, thermal) and 3D analytics (e.g., LiDAR, photogrammetry). The successful applicant will be pivotal in designing and executing experimental studies to capture high-dimensional plant and environmental data, aiming to develop scalable methods for assessing crop health and resource use efficiency.

This position offers a unique opportunity to collaborate with agronomists, plant breeders, data scientists, and engineers, driving innovation in precision agriculture and sustainable food production. In addition to AAGI, this position will service research needs of other UQ and The Grains Research and Development Corporation (GRDC) supported projects.

Key responsibilities will include: 

• Research:

  • Produce quality research outputs consistent with discipline norms by publishing or exhibiting in high quality fora.

  • Work collaboratively with AAGI, UQ and grains industry colleagues to deliver research, analytical support and teaching activities

  • Provide analytical support for research projects supported by AAGI and which are aligned with the expertise of the applicant

  • Contribute to transfer of knowledge, technology and practices to colleagues and to researchers within the Australian grains industry

  • 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. On an as-needs basis:

  • Provide feedback, coaching, and professional development to others in the research teams, including to Service and Support of AAGI investments

  • 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: Develop partnerships by cultivating relationships with the grains industry, government departments, professional bodies and the wider community, 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.

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.

• Completion or near completion of a PhD in the computer science or relevant field.

• Demonstrated experience with multi-modal imaging (RGB, thermal, spectral) and 3D data acquisition (e.g., LiDAR, structured light, photogrammetry).

• In-depth understanding of linear algebra and fundamentals of deep learning.

• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with latent variable models (e.g., CLIP, GLIP, MaskCLIP).

• Knowledge of Transferability in Machine Learning is desirable.

• Knowledge in Active Learning is desirable.

• Programming skills and experience with dataset annotation and management.

• Demonstrated success in collaboration in interdisciplinary team-work environments

• Evidence of publications in reputed refereed journals and presenting at conferences.

• Evidence of capacity to develop and deliver educational or training materials

• Demonstrated experience in successful supervision of undergraduate and/or higher degree research projects.

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

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.

For more information about this opportunity, please contact A/Prof Mahsa Baktashmotlagh m.baktashmotlagh@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.
 

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 talent@uq.edu.au for accessibility support or adjustments.

Applications close Thursday 22 May at 11.00pm AEST (R-49988). Please note applications will be reviewed as received. Candidates may be interviewed prior to the job closing date. We encourage candidates to apply as soon as possible.