Mode
Internal

Study As
Full Time

Principal Supervisor
Associate Professor Wolfgang Mayer

Main Campus
Mawson Lakes

Applications Close
01 Dec 2022

Study Level
PhD

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:
No project stipend available

About this project

Extracting useful information from natural language text remains a challenging task despite the considerable advances in machine learning technology for natural language processing in recent years. For example, the accuracy of state-of-the-art machine learning approaches for event extraction remains well below what humans can achieve in this task. Modern machine learning models produce results that are based predominantly on correlations of text passages and lack the understanding that humans who possess prior knowledge would attain. The challenge in machine learning and language processing has been to effectively utilise knowledge bases that exist about specific domains in learning. How to best combine the knowledge-based and learning from data paradigms remains an open research question.

This project will create novel machine learning methods that can incorporate domain-specific knowledge bases in a deep learning framework. It will investigate the effectiveness of infusing deep learning with prior knowledge on the correctness and completeness of information extraction from natural language text. It aims to validate the approach using case studies related to event extraction from natural language documents.

Outcomes will be a novel approach to incorporating prior knowledge into deep learning systems for natural language processing. This will help create machine learning systems that are more effective in acquiring meaningful specific information from natural language documents. The project will demonstrate the technology by developing a concrete application for extracting knowledge graphs about events and their relationships from natural language text. This task has broad applicability in many industries, as it facilitates intelligence gathering and analysis tasks in law enforcement, defence, financial industries, manufacturing and supply chains.

What you’ll do

In this project-based research degree, you will develop cutting-edge machine learning technology for information extraction and natural language processing, test the algorithms on case studies, and publish papers in premier research outlets. You will design machine learning technologies that make effective use of prior knowledge, build data pipelines for training the models, and compare them with other state-of-the-art approaches.

Artificial Intelligence and machine learning are highly sought skills and on completion of your studies, you will be prepared to advance your career in many industry sectors. This project is an ideal vehicle to develop your AI skills and achieve demonstrable outcomes and experience in machine learning technologies.

Where you’ll be based

Join a dynamic research environment of world-class researchers and a strong PhD cohort in UniSA’s Industrial AI Research Centre (IAI). Liaising collaboratively with our industry partners, we offer end-to-end holistic solutions that include artificial intelligence, mathematics, domain expert knowledge, and supporting software systems as integral components. 

Supervisory Team


Financial Support

This project is funded for reasonable research expenses. 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 $45,076 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$39,700 per annum (2023 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 projects selection criteria: 
  • Experience with machine learning tools such as Tensorflow and Pytorch
  • Experience with Python programming
Applicants who can also demonstrate the following will be highly regarded:
  • Experience with machine learning and natural language processing
  • Excellent spoken and written English

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 Thursday 1 December 2022.

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 research.admissions@unisa.edu.au. You will receive a response within one working day.

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