Organisation/Company UNIVERSITY OF SYDNEY Research Field Computer science Engineering Engineering Researcher Profile Leading Researcher (R4) Country Australia Application Deadline 7 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
- Full time, 8 month fixed term position. Located in the Rose Street Building (J04) on the Camperdown Campus
- Work with world-leading researchers in robotic sensing and perception
- Contribute to fundamental research in forest imaging and 3D deep learning
- Base Salary Level A Step 6 - 8 $113,400 - $121,054 p.a + 17% superannuation
About the opportunity
We are currently seeking a Postdoctoral Research Associate to undertake fundamental and applied research into novel deep learning approaches to analysing LiDAR and vision data in forest imaging and remote sensing. The role is part of a three-year project with SCION in New Zealand bringing together researchers in robotic perception, machine learning, remote sensing and silviculture to transform and upscale forest phenotyping operations.
The role will be supervised by Dr. Mitch Bryson, who currently leads the Forestry Research group within the Australian Centre for Robotics (ACFR), at the University of Sydney. The ACFR is one of Australia's leading robotics research groups, and the candidate will have the prospect to work closely with world-leading experts at the ACFR and with our project partners at SCION. The research will focus deep learning-based classification, segmentation and regression using combinations of high-resolution LiDAR point cloud data and image data and may draw upon aspects of synthetic data-based learning and domain adaptation.
To learn more about the Australian Centre for Robotics (ACFR), click here.
In this role you will:
- work closely with a team of academics and researchers as part of world-leading research program
- develop new techniques based on 3D sensor perception and deep learning to estimate forest tree structure from high-resolution drone-based LiDAR point clouds and imagery
- contribute to a world-leading large-scale forest phenotyping project
- disseminate your work at top international conferences and journals, and contribute as a researcher to project report preparation and presentation at workshops for project stakeholders.
About you
The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values. We are seeking an excellent candidate for a Postdoctoral Research Associate in 3D Deep Learning for Vision and Lidar position who has:
- a PhD (or near completion) in a relevant field
- background/skills in point cloud deep learning and/or 3D deep learning from images
- proven ability to conduct high quality research, evidenced by peer-reviewed publications
- a desire to work as part of a larger multi-disciplinary team in advancing applied research in 3D deep learning and forest science
- programming experience in Python and experience using deep learning tools such as PyTorch, Keras and/or Tensorflow
- ability to meet established project targets and deadlines, and excellent communication and interpersonal skills.
Sponsorship / work rights for Australia
You must have unrestricted work rights in Australia for the duration of this employment to be eligible to apply. Visa sponsorship is not available for this appointment.
Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.
Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.
For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.
For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Chris Masaoka, Recruitment Operations by email to.
The University reserves the right not to proceed with any appointment.
Applications Close - Tuesday 07 October :59 PM
#J-18808-Ljbffr
📌 Postdoctoral Research Associate in 3D Deep Learning for Vision and Lidar
🏢 Unist
📍 City of Sydney