PhD Scholarships in Underwater Situational Awareness

    • POSTED: June 8, 2023
    • CLOSES: Open until filled
    • LOCATION: Sydney, Australia
    • POSITION: PhD Scholarship
    • ORGANISATION: University of Sydney
    • SUPERVISOR: Professor Stefan Williams
    • PhD STIPEND: $40,000 AUD (Tax-Free)

    The Australian Centre for Robotics Marine Systems Group at the University of Sydney has three fully funded PhD positions open in distributed underwater surveillance systems for situational awareness in the marine environment, as part of the new Australian Robotic Inspection and Asset Management Research Hub, ARIAM.

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

    Autonomous and unmanned technologies are well established tools that are being used in the marine environment for a variety of tasks, including in scientific exploration, resource extraction and management and defence applications. This project aims to develop distributed underwater surveillance systems comprised of a network of fixed and mobile acoustic receivers complemented by observations collected from remote sensing and in-situ assets, including autonomous surface and underwater vessels, that are tightly integrated to provide situational assessment in the marine environment.  Recent work in the oceanographic community has seen the deployment of thousands of drifting floats to help measure temperature, depth and salinity profiles while providing invaluable ground truth information for validating global ocean circulation models.  We foresee a significant opportunity on a more local scale to develop tools and techniques that will allow observations from a team of distributed acoustic receivers to be integrated to localise targets of interest in the environment.

    Depending on interest and ability, candidates will investigate one or more of:

    • Machine learning based on-board autonomous target tracking and classification tools that can be used in real-time to identify and track one or more acoustic sources. These algorithms should be capable of being run on data being collected onboard a vessel to enhance traditional manual data analysis but should also be capable of being run on embedded hardware with the potential for tracking information to be processed locally but shared with a distributed array of receivers.
    • Distributed beamforming techniques to simultaneously localise an array of acoustic receivers and potential targets based on acoustic information received by the array elements.  The developed techniques will need to operate in a low-bandwidth environment, limiting the amount of information that can be shared amongst the nodes.
    • Planning deployment and recovery of mobile acoustic receivers to increase the observability of targets.  This work will exploit decentralised multi-robot planning tools that allow the proposed system to schedule launch, tracking, recovery, servicing, and coordinated path planning of one or more autonomous vehicles designed to deploy and recover mobile receivers, including AUV and drifting acoustic receivers.  These plans must deal with potentially large uncertainties in the location of the drifter and adapt to loss of assets.
    • Management of deployed autonomous system assets. Despite the recent advances in Uncrewed Underwater Vehicles (UUV) and related technologies, these platforms typically have limited levels of autonomy and generally do not operate in a collaborative manner.  In order to increase the efficiency and effectiveness of survey operations, some level of in-mission adaptation (e.g. trajectory, speed, altitude or active sensors) is required to allow a team of vehicles to respond to the data they are collecting while underway.  This work aims to develop novel planning and acoustic communication schemes that exploit developments in machine learning, network, and communication theory and represents a step towards truly effective surveying using AUV systems.

    The outcomes of this project will be of considerable interest in the context of operations monitoring marine environments for potential naval threats, including covert autonomous systems, but will also be applicable in civilian applications for maintaining offshore assets as well as tracking animals, including whales and other cetaceans, shipping traffic and for environmental monitoring purposes.

    Research Environment

    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 leading Australian universities: The University of Sydney, QUT and ANU. These projects will be supervised by Professor Stefan Williams, who leads the Australian Centre for Robotics (ACFR) Marine Systems Group at the University of Sydney.

    The ACFR is the largest robotics and automation research group in Australia and is one of the largest in the world. For over 20 years the ACFR has been a leader in research and training in field robotics, with programs in agriculture, intelligent transportation systems including autonomous driving, and in marine robotics including an ongoing benthic monitoring program operating multiple ROVs and AUVs. The ACFR offers specialised imaging labs and facilities, robotic platforms, test tanks 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 ACFR is part of The University of Sydney which offers a rich academic setting in a world-class city.

    The Marine Systems Group hosts a medium test tank for developing novel underwater scene reconstruction techniques.  We have access to a broad range of underwater robotic systems.

    • BlueROV2 platforms equipped with stereo imaging and Reach Robotics manipulator
    • AUV platforms for high resolution seafloor imaging
    • Unmanned Surface Vessel
    • Sensors including imaging, sonar and positioning systems

    Thales is a global leader in underwater systems and the world’s top exporter of sonars and related systems for naval forces. Thales’ Underwater Systems division are headquartered in Sydney and undertake research and development related to a variety of sonar systems.  Thales also offer navigation systems, radars and air traffic control centres, surveillance systems, satellite navigation products, and airport management solutions.

    The three roles advertised here are part of a larger opportunity that will hire and bring together a large group of PhD students and multiple Postdocs. For more on ARIAM, our partners, and opportunities to join the hub please visit the ARIAM Research Hub website.


    Three fully funded 3.5-year PhD scholarship covering tuition fees and stipend of $40,000 (tax-free).

    About You

    Successful candidates will have:

    • A bachelor’s degree in a relevant discipline
    • Interest in robotics research for perception or perception enabled control with direct impact in an entrepreneurial, dynamic industry
    • Excellent communication and interpersonal skills
    • Creativity, curiosity, and passion
    • Experience with one or more of mechatronics, computer vision, machine learning, control
    • Hands-on experience with robotic platforms, ROS, Python, C++, and/or deep learning frameworks would also be an asset

    How to Apply

    To apply, please use the application form below and include the following:

    • CV
    • Unofficial transcripts
    • Cover letter

    Optional but appreciated – 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 developing technology
    • A description of a project that you’re proud of, or plan to be when completed

    Internatonal 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 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.

    For Further Information


    Job Application

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