Job

Postdoctoral Research Associate in 3D Robotic Vision

  • Join a world-leading research hub developing intelligent robotic systems for inspection and asset management
  • Develop novel imaging technologies to allow robots to see robustly and efficiently in a broad range of challenging conditions
  • Full time, 3 year fixed term position, Level A, Base Salary $105K + 17% superannuation
  • POSTED: December 11, 2023
  • CLOSES: Closed
  • LOCATION: Sydney, Australia
  • POSITION: Postdoctoral Research Associate
  • ORGANISATION: University of Sydney
  • SUPERVISOR: Dr. Donald Dansereau

About the opportunity

ARIAM Hub is a collaboration between leading academic researchers and experts from the Australian robotics industry supported by the Australian Research Council to deliver research excellence in robotics for asset management. ARIAM spans 3 renowned  Australian universities: The University of Sydney, QUT and ANU. This position will be supervised by Dr Donald Dansereau, head of the Robotic Imaging Lab 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 Robotic Imaging Lab is focused on endowing machines with new ways of seeing the world.

We are expanding our team and have multiple positions opening as part of ARIAM. We are currently seeking an ambitious and talented Postdoctoral Research Associate to undertake fundamental and applied research in novel computer vision approaches to high-fidelity drone-based 3D reconstruction of buildings and infrastructure. As part of the Australian Robotic Inspection and Management Research Hub (ARIAM), this position involves working closely with Hub Industry Partner Trendspek on their precision asset modelling and intelligence technology. As part of the research hub you will have opportunities to travel and collaborate with our partners across Australia.

Our current research will focus on combining novel scene representations and computational imaging approaches to enable greater performance in modelling visually challenging scenes from drone-based imagery. Depending on interest and ability there is also scope to develop novel imaging technologies to further improve performance.

This robotic vision-focused position will advance the 3D reconstruction technology required for modelling complex 3D infrastructure. Key challenges include complex appearance due to reflective and transparent surfaces, complex geometries, and dense occlusion from vegetation.

Depending on ability and interest, candidate approaches can include combining representations and visual processing from the graphics and vision communities, including inverse rendering and novel visual and geometric representations, and novel computational imaging devices and algorithms. This project will offer dramatic improvements in sensing robustness and performance, and geometric and textural accuracy in drone-based 3D asset inspection.

In this role you will:

  • work closely with a team of project academics, engineers, and PhD students
  • develop and characterise novel robotic vision representations, algorithms and/or imaging technologies
  • contribute to the ARIAM Hub’s demonstrator program that will showcase your research and that of other Hub projects
  • contribute as a researcher to project report preparation, presentation at internal workshops, and dissemination at top international conferences and journals as well as via internal workshops and presentations.

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:

  • skills relevant to robotic imaging in visually challenging conditions, outstanding candidates with skills in robotics including navigation, planning, and active perception are also strongly encouraged to apply
  • a PhD (or near completion) in a relevant field
  • knowledge of computer vision technologies including approaches to visual 3D reconstruction
  • knowledge of appearance-based scene representations including light fields and neurally regressed radiance fields would be an asset
  • a desire to advance 3D reconstruction from drone-based imagery using novel scene representations, visual processing, and computational imaging techniques
  • experience with one or more programming languages (C, C++, C#, Python, Matlab)
  • proven ability to conduct high quality research, evidenced by peer-reviewed publications
  • an ability to coordinate multiple project objectives to meet established targets and deadlines
  • excellent communication and interpersonal skills
  • hands-on experience with robotic platforms, ROS, and/or deep learning frameworks (Tensorflow and others), and OpenCV would be an asset
  • a history of research excellence evidenced by prizes or awards, relative to experience, would be an asset

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 which 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. Female candidates are strongly encouraged to apply for this position.

How to apply

Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the University of Sydney’s Workday site via the link below.

Please also include a Google Drive link to a 2-minute selfie video covering the following:

  • Your strongest engineering skills,
  • What do you enjoy most about research, and
  • A description of a project that you’re proud of, or plan to be when completed

If you are a current employee of the University or a contingent worker with access to Workday, 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.

For specific enquiries about the role, please contact Dr Donald Dansereau by email to donald.dansereau@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.


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