Postdoctoral Platform Fellow - Data/Machine Learning Analyst for Plant Phenomics
* The University of Queensland
* Australia, QLD
* May 27, 2026
Full-time
About The University of Queensland
For more than a century, The University of Queensland (UQ) has created positive change for society by delivering knowledge leadership for a better world. UQ ranks among the world's top universities, as measured by several...
Base salary will be in the range $83,698.91 - $111,431.10 + 17% Superannuation (Academic Level A)
The University of Queensland is strengthening its national research capability in plant phenomics through its participation in the Australian Plant Phenomics Network (APPN). Established under the National Collaborative Research Infrastructure Strategy, APPN provides cutting-edge infrastructure and expertise to advance agricultural productivity across Australia's diverse production environments. UQ joined APPN in 2024, creating new opportunities for ambitious researchers to work at the intersection of advanced sensing technologies, computation and plant science.
Working under the broad direction of the UQ Node Director, you will contribute specialist expertise in high‐throughput and 3D plant phenotyping, support delivery of national research infrastructure, and play a leading role in developing APPN capabilities at UQ. The role combines hands-on research, platform leadership and collaboration with industry, government and academic partners in a dynamic, multidisciplinary environment.
Key responsibilities include:
Providing specialist research expertise in proximal sensing and high‐throughput plant phenotyping methods to support agronomy, broadacre crop physiology and trait pre‐breeding. projects.
Leading 3D imaging, point cloud analysis and simulation studies, including design of experiments, data analysis and preparation of research outputs for publication.
Managing and overseeing deployment of UAV and ground‐based phenotyping platforms for field and controlled‐environment research trials.
Supporting the effective operation of APPN at UQ through training, supervision, technical troubleshooting, reporting and compliance with WHS and regulatory requirements.
Research Focused
You will contribute to high‐quality, impactful research outcomes through methodological innovation, data analysis, peer‐reviewed publication and engagement with national and international collaborators.
Citizenship and Service
You will demonstrate responsible research conduct, contribute to team culture, support shared infrastructure, and engage constructively with clients and stakeholders of the APPN‐UQ node.
You will bring advanced technical expertise, intellectual curiosity and collaborative leadership to this nationally significant research platform. You will demonstrate:
Completion of a PhD in 3D‐based phenotyping analytics or a closely related field, or an equivalent combination of relevant qualifications and at least four years' experience in plant phenomics.
Demonstrated expertise in designing, managing and analysing 3D plant‐based point models and spatial datasets within research or institutional environments.
Strong capability in mathematical and statistical programming languages such as R and Python, with experience developing and using 3D models.
A strong record of research outputs through publications in peer‐reviewed journals and conference proceedings.
Advanced knowledge of precision agriculture technologies and experience handling complex, high‐volume datasets.
Excellent communication, consultative and interpersonal skills, with the ability to work effectively across multidisciplinary research teams and external partners.
A current Remote Pilot Licence (RePL).
Demonstrated problem‐solving capability and leadership experience within research or teaching environments.
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. 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 greaterbenefits of joining the UQ community are broad: from being part of aGroup 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,access to exclusive internal-only vacancies,and genuine career progression opportunities via the academic promotions process.
Interested?
For more information about this opportunity, please contact Carla Gho Brito, carla.gho@uq.edu.au. For application inquiries, please reach out to the Talent Acquisition team attalent@uq.edu.au ,statingthe job reference number (below)in the subject line.
When you apply, pleaseensure you uploadaresume,cover letter, andresponses to the 'About You' section.Please note that applications received via email will not be accepted.
Other Information
Pre-employment checksmayincludeverification of theright to work in Australia and qualifications. This may also include checks relating to gender-based violence matters or other integrity and conduct requirements.
Relocating from interstate or overseas? We may support you with obtaining employer-sponsored work rights and a relocation support package, however upfront costs will still be expected to be covered.You can find out more about life in Australia's Sunshine State here .
We'rededicated toequity, diversity, and inclusion. Werecognise that career pathways and opportunitiesdiffer, andencourage applications from candidates who may not meet everycriteriabut candemonstratetheir potentialrelativeto opportunity.We'realso happy to support any accessibility needs throughout the recruitment process. Just let us know how we can help by emailingtalent@uq.edu.au or calling +61 7 3365 2623.
Applications closeWednesday 24 June 2026 at 11.00pm AEST (R-63960).
#J-18808-Ljbffr