PhD Scholarship in Aerial Computer Vision (2 scholarships)
- POSTED: May 5, 2023
- CLOSES: Open until filled
- LOCATION: Sydney, Australia
- POSITION: PhD Scholarship
- ORGANISATION: University of Sydney
- SUPERVISOR: Dr Mitch Bryson
- PhD STIPEND: $40,000 AUD (Tax-Free)
Fully-funded Ph.D. Scholarship Opportunities in Aerial Computer Vision
The Australian Centre for Robotics at the University of Sydney currently has two fully funded Ph.D. positions open in the areas of computer vision/deep learning-based change detection and 3D modelling using aerial images. The projects are a part of the new Australian Robotic Inspection and Asset Management research hub, ARIAM in collaboration with Nearmap.
Two fully-funded 3.5-year Ph.D. scholarships, covering tuition fees are on offer. Applicants with a strong background in Machine Learning, Computer Vision, Computer Science, Mechatronic Engineering, Electrical and Computer Engineering or similar programs are encouraged to apply.
The project aims to develop new approaches using machine learning and computer vision to reconstruct measurable 3D objects from multi-angle imagery, and model longitudinal changes to the status of objects in imagery in the presence of noisy signals. Successful candidates will work closely with our research partner, Nearmap, to provide cutting-edge solutions to modelling and understanding high-resolution aerial images captured over urban environments.
Research Environment
Australian Centre for Robotics (ACFR)
The projects are hosted at the ACFR within the University of Sydney, one of Australia’s leading robotics research centres. The ACFR has a twenty-five-year history of quality, internationally-recognised research in robotics, sensing and perception with extensive collaboration and impact with industrial partners in agriculture, mining, transport, aviation, marine science, forestry, amongst others. The ACFR provides a supportive research environment with access to senior researchers and academics in robotic systems and state-of-the-art facilities to support the project. We provide opportunities for HDR students to engage in research projects that have significant impact on real-world problems, through our extensive collaborations with industrial and applied research partners. The University of Sydney offers a rich academic setting in a world-class city, and the ACFR has strong ties to a network of nearby and international academic and industrial collaborators.
Nearmap
Successful candidates will work closely with our partner Nearmap, a leading next-generation location intelligence company. Nearmap designs and builds world leading aerial camera systems, collects and provides high-resolution aerial imagery in four countries (covering 95% of the population of Australia, 85% in USA, and coverage in NZ and Canada), produces city scale 3D reconstructions, and develops data-driven AI solutions to interpret information and insights for its users (such as in government and property insurance). Using highly customised deep learning architectures, Nearmap processes imagery on the scale of tens of petabytes with compute clusters running thousands of nodes. Nearmap uses technologies such as Kubernetes, PyTorch and a wide range of geospatial and scientific python libraries, and is looking for highly motivated and talented PhD students to partner with some of their most exciting and innovative technical work. The successful candidates will have access to Nearmap’s extensive imagery database, including historical imagery, and state-of-the-art AI and machine learning tools and infrastructure to support the project.
ARIAM Research Hub
ARIAM is a new research group and 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. As part of the ARIAM Research Hub, you will be a part of a wider network of academic and industry collaborators. ARIAM spans 3 leading Australian universities: The University of Sydney, Queensland University of Technology and The Australian National University. The two roles advertised here are part of a larger opportunity bringing together a new collective of Ph.D. students and Postdoctoral researchers.
About You
Successful candidates will have:
- A bachelor’s degree in a relevant discipline
- An interest in seeing your research have a direct impact in industrial applications and enhance the way we measure and understand the world from geo-spatial observations
- Excellent communication and interpersonal skills
- Creativity, curiosity, and passion
- Prior experience in machine learning, image processing and/or computer vision is desirable
How to Apply:
To apply, use the form inserted below and include the following:
- CV
- Unofficial transcripts
- Cover letter
Please also include a Google Drive link to a two-minute selfie video covering the following:
- Your strongest engineering or computer science skills
- What do you enjoy most about developing technology
- A description of a project you have worked on that you’re proud of (or plan to be) when completed
International Applicants:
Both domestic and international applicants are welcome. The Australian Ph.D. is a 3.5-year program, generally with direct entry from an undergraduate degree with a final-year thesis project (see Admission Criteria below).
Candidates complete a total of two graduate-level classes of their choice as part of the Ph.D. program. There are no doctoral qualifying / candidacy exams. Candidates complete a viva / oral thesis defence at the completion of the program.
Admission Criteria:
Successful candidates will need to enrol in the University of Sydney’s Doctor of Philosophy (Engineering) program. Enrolment requirements are listed on the University website (https://www.sydney.edu.au/courses/courses/pr/doctor-of-philosophy-engineering.html).
Key requirements are:
- An Undergraduate or Master’s degree with overall first-class Honours or equivalent, AND
- Some sort of research experience, either:
- Completion of an Undergraduate degree with a final-year thesis/project, OR
- Completion of a Master’s by research degree, OR
- Completion of a Master’s by coursework degree with a substantial research project.
Further Information:
For any questions please email mitch.bryson@sydney.edu.au.