Degree type
PhD
Closing date
1 April 2025
Campus
Launceston
Citizenship requirement
Domestic
Scholarship
$52,000pa for 3.5 years
About the research project
Autonomous Underwater Vessels (AUVs) have recently seen major development activities both in Australia and globally. As communication is severely restricted when the AUV is submerged, there has been an interest in the use of modern Machine Learning and Artificial Intelligence (ML/AI) capabilities to allow the AUV to operate without input from a crewed vessel.
A major benefit of an AUV remaining submerged is to limit detected while conducting survey activity, and in that situation the ability for the AUV to make autonomous decisions which will enhance the data collection activity of the survey is extremely valuable.
There are several locally made AUVs that are commercially available ranging from large and extra-large units like the Ghost Shark being manufactured by Anduril Australia, and the Speartooth developed by C2 Robotics, to the mini-AUV the Hydrus developed by Advanced Navigation. These platforms all include a range of sensors that allow the collection and analysis of optical, audio and other environmental data.
As various AUVs become more affordable we are also seeing the possibility of the deployment of multiple vessels that can collaborate with each other to enhance data collection and processing capabilities.
While these platforms will all support various degrees of machine learning there is a need to develop models that can be used to support these systems in adapting mission tasking to adapt to unforeseen situations.
With limited means for communication, it is not feasible for a vehicle to share raw data. There is need for a model in which individual agents can generate efficient data products that can be more easily shared to a supervisory vessel, or team member to enable adaptive mission tasking.
Primary Supervisor
Funding
The successful applicant will receive a scholarship which provides:
- a living allowance stipend funded by the Next Generation Graduates Program of $52,000 per annum for 3.5 years
- a relocation allowance of up to $2,000
- a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)
As part of the application process you may indicate if you do not wish to be considered for scholarship funding.
Other funding opportunities and fees
For further information regarding other scholarships on offer, and the various fees of undertaking a research degree, please visit Scholarships and fees.
Eligibility
Applicants should review the Higher Degree by Research minimum entry requirements.
Ensure your eligibility for the scholarship round by referring to our Key Dates.
Additional eligibility criteria specific to this project/scholarship:
- Applicants must be able to undertake the project on-campus
- The domestic applicant must be an Australian citizen.
Selection Criteria
The project is competitively assessed and awarded. Selection is based on academic merit and suitability to the project as determined by the College.
Additional essential selection criteria specific to this project:
- Strong background in engineering.
- Strong computational skills.
- Research and Analytical skills.
Additional desirable selection criteria specific to this project:
- Experience with AI, ML, and/or Autonomy.
- Software design or programming.
Application process
- Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
- Contact Dr Peter King to discuss your suitability and the project's requirements; and
- In your application:
- Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
- Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
- Apply prior to 1 April 2025.
Full details of the application process can be found under the 'How to apply' section at Research degrees.
Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.
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