Study As
Full Time

Principal Supervisor
Associate Professor Dhika Pratama

Main Campus
Mawson Lakes

Applications Close
30 Jan 2023

Study Level

Applications Open To
Domestic Candidate or International Candidate

Tuition Fees:
All domestic students are eligible for a fee waiver. International students who receive a stipend are eligible for a fee waiver. Find out more about fees and conditions.

Project Stipend:
$29,863 p.a. available to domestic and international applicants

About this project

Use artificial intelligence to improve forecasting 

Are you passionate about a career in artificial intelligence and keen to innovate forecasting methods? The University of South Australia – Australia’s University of Enterprise – is offering a dynamic project-based PhD with real industry impact within our Industrial AI Research Centre.

Although time-series forecasting has been studied intensively, existing approaches are limited to short-term forecasting and often result in expensive errors. Existing approaches exclude demand-side variables, which are much more volatile than supply-side indicators. In other words, existing approaches are inapplicable in changing environments or require expensive recalibrations under non-stationary conditions. 

Our project aims to develop AI-based long-term time-series forecasting approaches in dynamic conditions. It considers a dynamic environment in which a model is not kept static once built. Instead, it is continuously adjusted in memory-wise fashion so that it never becomes outdated in the presence of changes. 

We also address transferability, making it possible for a model to be transferred to different but related problems with negligible costs. 

The aim is for the project outcomes to not only improve planning, policymaking and smart investment, but also contribute to increased productivities and efficiencies.

You will join a vibrant cohort within the Industrial AI Research Centre. The Centre has a world-class reputation for industry engagement of AI technologies and you will benefit from outstanding equipment, facilities and the experience of your colleagues. Your supervisory panel has a strong publication track record and has secured sizeable government funding in renewable energy areas.

What you’ll do

In this project-based research degree, you will conduct both fundamental and applied research. You will develop novel deep learning algorithms to solve different variants of LTTSF problems. The proposed deep learning technologies will be applied to renewable energy use cases of industry partners and will be validated with real-world industry datasets. 

You will receive intensive research training in AI/AML as well as hands-on experience in handling real-world datasets. Upon completion you will also have expertise in programming tools (Pytorch, Tensorflow, Keras) and their relevant libraries. The project gives you the opportunity to gain solid experiences in industry-ready software development as well as end-user engagements. 

You will be encouraged to publish the outputs of this project in high ranking journals, and deliver presentations to industry partners.

The project requires direct engagement with an industry partner and you will receive mentorship from both academics and industry practitioners. This invaluable experience will not only help build your professional network but position you well for employment post-graduation. 

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.

Supervisory Team

Financial Support 

This project is funded for reasonable research expenses. Additionally, a living allowance scholarship of $29,863 per annum is available to eligible applicants. Australian Aboriginal and/or Torres Strait Islander applicants will be eligible to receive an increased stipend rate of $46,653 per annum (2023 rates). A fee-offset or waiver for the standard term of the program is also included. For full terms and benefits of the scholarship please refer to our scholarship information for domestic students or international students.

Eligibility and Selection 

This project is open to application from both domestic and international applicants.

Applicants must meet the eligibility criteria for entrance into a PhD. All applications that meet the eligibility and selection criteria will be considered for this project. A merit selection process will be used to determine the successful candidate.

The successful applicant is expected to study full-time and to be based at our Mawson Lakes Campus in the north of Adelaide. Note that international students on a student visa will need to study full-time.

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, 30th of January 2023.

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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