{"id":139844,"date":"2023-09-20T03:00:45","date_gmt":"2023-09-20T01:00:45","guid":{"rendered":"https:\/\/www.cde.ual.es\/?p=139844"},"modified":"2023-09-19T12:14:34","modified_gmt":"2023-09-19T10:14:34","slug":"postdoctoral-research-associate-in-3d-robotic-vision-in-australia","status":"publish","type":"post","link":"https:\/\/www.cde.ual.es\/en\/postdoctoral-research-associate-in-3d-robotic-vision-in-australia\/","title":{"rendered":"Postdoctoral Research Associate in 3D Robotic Vision in Australia"},"content":{"rendered":"

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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\u00a0Robotic Imaging Lab<\/a>\u00a0within the Australian Centre for Robotics (ACFR<\/a>) 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.<\/p>\n

They are expanding their team and have multiple positions opening as part of ARIAM<\/a>. They 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<\/a>), this position involves working closely with Hub Industry Partner\u00a0Trendspek<\/a>\u00a0on 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.<\/p>\n

Their 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.<\/p>\n

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.<\/p>\n

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.<\/p>\n<\/div>\n<\/div>\n

Requirements<\/strong><\/p>\n

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\u00a0Postdoctoral Research Associate\u00a0<\/strong>position who has:<\/strong><\/p>\n