Study As
Full Time

Principal Supervisor
Associate Professor Ady James

Main Campus
Mawson Lakes

Applications Close
08 Jul 2024

Study Level

Applications Open To
Domestic Candidate or International Candidate

Tuition Fees:

All domestic students are eligible for a fee waiver. Find out more about fees and conditions.

Project Stipend:
No stipend available

About this project

Harness generative AI to improve model-based system engineering

If you are excited about launching your career in artificial intelligence and motivated to develop novel applications for the defence industry, the University of South Australia – Australia’s University of Enterprise – is offering a hands-on project-based PhD with national impact within the Industrial AI Research Centre in partnership with external partners.

Model-Based Systems Engineering (MBSE) has good potential to decrease costs and enhance the quality of systems and acquisition processes. MBSE makes engineering projects more efficient, accurate, and collaborative, making it a highly promising approach. 

However, MBSE has encountered various barriers within both defence and non-defence organisations. These barriers can be broadly categorised into cost and complexity factors. Artificial intelligence (AI), especially generative AI, presents a promising avenue to address and overcome these barriers. 

Generative AI algorithms, for instance, are capable of automating the initial stages of model development by thoroughly analysing requirements from text-based documents and swiftly generating initial system models. This significantly reduces the time and effort required to initiate the MBSE process, making it more accessible and appealing to use.

Our project will determine existing frameworks and analyse the barriers to adopting MBSE. We will then identify where AI can best be utilised and develop a framework which both defence and non-defence organisations can use to implement MBSE. By working on this project, you will be working at the cutting edge of MBSE and pioneering a new generation of AI tools within that practice.  

You will be based within the Industrial AI Research Centre, working amongst a multidisciplinary team of industry-focused experts. Specifically, you will join the collegial and supportive Science, Technology, Engineering and Maths cluster. Your supervisory team are experts in AI, visualisation, systems engineering, and space engineering so you are sure to benefit from their world-class guidance and mentorship.  

What you’ll do

In this project-based research degree, you will conduct in-depth research into AI applications in MBSE, and existing frameworks and best practices. You will also analyse the barriers to MBSE adoption and identify key areas where AI integration can be most effective.

We will support you to develop a robust framework that integrates generative AI into MBSE processes. This includes designing methodologies, algorithms, and tools to facilitate seamless AI-assisted model development and system optimisation.

You will then collaborate with select defence and non-defence organisations to implement the AI-infused MBSE approach in a real-world context. You will be responsible for gathering data and feedback to evaluate the approach’s effectiveness and address any issues encountered.

There are opportunities for you to present your work at conferences interstate or overseas, strengthening your communication and networking skills and abilities.

Where you’ll be based

You will be based in the Industrial AI Research Centre. The Centre brings together experts from across computer sciences to develop solutions for autonomous and augmented intelligence systems. We are a part of the global revolution in artificial intelligence, machine learning, Industry 4.0 and Internet-of-Things (IoT) technologies. 

Our researchers work with organisations around the world to develop solutions that cater to their specific needs. We have worked with Siemens, BP Australia, Yokogawa Electric and more, growing these partnerships over time to continually design sophisticated AI-driven solutions. Financial Support

This project is funded for reasonable research expenses but no stipend is available

A fee offset for the standard term of the program is available to Australian and New Zealand citizens, and permanent residents of Australia, including permanent humanitarian visa holders. Additionally, any Australian Aboriginal and/or Torres Strait Islander applicant who holds an offer of admission without a living allowance will be eligible for the Aboriginal Enterprise Research Scholarship. This scholarship is to the value of $50,291 per annum. Any Aboriginal Enterprise Research Scholarship recipient will also receive a fee waiver. 

Where an international applicant holds an external scholarship or sponsorship a full or partial fee waiver may apply in some circumstances for exceptional applicants. Other international applicants will be required to pay full tuition fees of approximately AUD$41,700 per annum (2024 rates). 

Eligibility and Selection

This project is open to applications from both Domestic and International applicants. 

Applicants must meet the eligibility criteria for entrance into a PhD. Additionally applicants must meet the project selection criteria:
  • Hold an undergraduate degree in Software Engineering, Data Analytics or a related engineering/mathematics discipline
  • Experience with coding and working with modelling and simulation
All applications that meet the eligibility and selection criteria will be considered for this project.

The successful applicant is expected to study full-time and to be based at our Mawson Lakes campus in the north of Adelaide.

Essential Dates

Applicants are expected to start in a timely fashion upon receipt of an offer. Extended deferral periods are not available. Applications close on Monday 8 July 2024.

How to apply:

Applications must be lodged online, please note UniSA does not accept applications via email.

For further support see our step-by-step guide on how to apply , or contact the Graduate Research team on +61 8 8302 5880, option 1 or email us at You will receive a response within one working day.

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