CLOSED: Fully Funded PhD Scholarship: Light Field Imaging for Autonomous and Assisted Driving

Note that this position is now closed.

The Robotic Imaging Lab at the University of Sydney, Australia has a fully funded PhD position open in light field imaging for autonomous and assisted driving, in partnership with Ford Motor Company.

Applicants with a strong background in Mechatronic, Electrical, or Computer Engineering, Computer Science, or similar programs are encouraged to apply.

This project will develop light field imaging approaches to enable next-generation performance in autonomous driving and advanced driver assistance systems.

Challenges arise in devising long-range and wide-field-of-view 3D sensing solutions that offer low latency and operate under a wide variety of illumination and weather conditions.

The project's aims include:

• Designing and evaluating LF camera architectures suited to the challenges of autonomous and assisted driving,
• Developing computationally efficient 3D vision pipelines that exploit the rich information that LF cameras capture to deliver next-generation robustness and performance, and
• Running lab and field trials to rigorously evaluate novel sensing technologies for autonomous and assisted driving.

Depending on interest and ability, there is an opportunity to explore novel optics for light field capture and/or digital architectures for low-power low-latency light field vision.

Embedded in the Australian Centre for Field Robotics, the Robotic Imaging Lab is focused on endowing robots with new ways of seeing their world. From photons to actions, we employ computational imaging techniques to jointly consider the optics, low-level vision, and high-level semantic understanding that ultimately drive autonomous decision making.

The ACFR offers specialised imaging labs and facilities, robotic platforms including a range of autonomous passenger vehicles, and robotic field labs across on-campus and nearby off-campus sites. You will have access to mechanical and electronics workshops and a pool of technical staff to help realise your research ambitions. 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.

A fully funded 3.5-year PhD scholarship covering tuition fees and a stipend covering living expenses.

About You

Successful candidates will have:

• A bachelor’s degree in a relevant discipline
• Interest in light field imaging and robotics research
• Excellent communication and interpersonal skills
• Experience with one or more of imaging, image processing and/or computer vision
• Hands-on experience with embedded processing, FPGA development, ROS, Python, C++, and/or deep learning frameworks would also be an asset

How to Apply

Application deadline EXTENDED to 22 Jun 2022 midnight (Sydney time)

To apply, please email donald.dansereau@sydney.edu.au, with the subject line “LF Driving PhD Application:” and your name. Include the following:

• CV
• Unofficial transcripts
• Cover letter

Please also include a link to a 2 minute video covering the following:

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

International Applicants

Domestic and international applicants are welcome. The Australian PhD 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 PhD 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 here. Key requirements are:

• An Undergraduate or Master's degree with overall grade of at least 75% or equivalent GPA, 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.

For Further Information

This Robotic Imaging Lab Website
Sydney Institute for Robotics and Intelligent Systems
Australian Centre for Field Robotics
For any questions please email donald.dansereau@sydney.edu.au.