• Work with world-leading researchers in robotic sensing and perception

• Contribute to fundamental research in forest imaging and 3D deep learning

• Full time, 17 months fixed term position, Level A, Base Salary $105K - $109K + 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 opportunity 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 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

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

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.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community that reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

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 support filling out this application, please contact Rebecca Astar or Cherie Goodwin, Recruitment Operations, by email to recruitment.sea@sydney.edu.au.

© The University of Sydney

The University reserves the right not to proceed with any appointment.

Click to view the Position Description for
this role.

Applications Close