Postdoctoral Research Associate in 3D Deep Learning for Vision and Lidar at GDG on Campus | University of Sydney

Darlington, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 25

Salary

121054.0

Posted On

23 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

3D Deep Learning, LiDAR, Vision Data, Forest Imaging, Remote Sensing, Point Cloud Deep Learning, Python, PyTorch, Keras, TensorFlow, Classification, Segmentation, Regression, Synthetic Data, Domain Adaptation, Communication, Interpersonal Skills

Industry

technology;Information and Internet

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 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 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. 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 are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion, evidenced by 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 LGBTQIA+. We welcome applications from candidates from all backgrounds. We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Platinum Employer. Find out more about our work on diversity and inclusion. 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 any documents in alternate formats, please contact Chris Masaoka, 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 Tuesday 07 October 2025 11:59 PM Our team is expanding, and we want to hire the most talented people we can. Continued success depends on it! So once you've had a chance to explore our current open positions, apply to the ones you feel suit you best and keep track of both your progress in the selection process, and new postings that might interest you! The University values are excellence, trust and accountability. The University of Sydney is committed to diversity and social inclusion. Applications from people of culturally and linguistically diverse backgrounds; equity target groups including women, people with disabilities, people who identify as LGBTIQ; and people of Aboriginal and Torres Strait Islander descent, are encouraged. The University reserves the right not to proceed with any appointment. The University of Sydney may conduct routine pre-employment checks before an appointment is made. Want to know more about working at the University of Sydney? https://www.sydney.edu.au/about-us.html

Responsibilities

The role involves conducting fundamental and applied research into novel deep learning approaches for analyzing LiDAR and vision data in forest imaging. The candidate will develop new techniques for estimating forest tree structure and contribute to a large-scale forest phenotyping project.