Mode
Internal

Study As
Full Time

Principal Supervisor
Professor Thuc Le

Main Campus
Mawson Lakes

Applications Close
20 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 stipend available

About this project

Using data science to improve employment success for people with a disability

If you are seeking to advance your career in data science and are interested in helping people to achieve a better life, the University of South Australia - Australia’s University of Enterprise – is offering a unique opportunity for a PhD project at our Data Analytics Group in partnership with Maxima Training Group (Aust) Limited to provide recommendations on achieving greater employment success for people with a disability. 

Sustainable employment of people with disability, has posed a major challenge for industrialised societies. In Australia, even though the government has implemented the Disability Employment Services (DES) sector, to provide employment assistance to job seekers with disability, only 53 per cent of people with disability are employed. This is in sharp contrast to 84 per cent of those without a disability. Additionally, people with a disability are under-represented in employment and have longer periods of unemployment. 

Most job seekers seek advice from employment consultants on which factors they should improve to increase their employment success. Depending on the profile of a job seeker, there are many options to consider, such as obtaining a training diploma, improving communication skills, or simply getting a driver’s licence. 

Currently, most recommendation systems employed by DES rely on traditional models, where the desired outcome, instead of the degree of outcome improvement, is the main goal for optimisation. In this project you will use data analysis to review which factors to significantly improve the employability of people with a disability.

There is a growing demand for professionals with expertise in data science, and in this project, you will gain the expert knowledge to meet that demand and help people achieve a better and more equitable life.

What you’ll do

In this industry partnered project, you will develop causality-based approaches to tackle the recommendation problem in the disability employment sector, aimed at providing greater employment outcomes. Specifically, during your research project you will help identify the relevant factors that achieve the greatest improvement in employment potential, informing policy and practice.

The acquired skills and their direct application in this industry-driven project will prepare you to be a leader in the field of data science, with practical experience and skills in the sought-after area of data and statistical analysis.

After finishing the project, the PhD graduate will have strong research skills in the area of Data Science as well as industry experience. They will be ready for the job market in both academia and industry. The student will work with both researchers in data science, statistics, and the industry partner on the project.

Where you’ll be based

You will be based at Industrial AI research centre, which brings together experts from across data analytics and data management. We are a leader in the field of data science and bioinformatics, our research has been supported by nine Australian Research Council (ARC) Discovery Grants. We focus on data mining, predictive modelling, machine learning, and bioinformatics, and our outcomes are regularly published in top international journals.

Principal Supervisor, Associate Professor Thuc Le is currently a DECRA fellow in bioinformatics at UniSA STEM, and the leader of bioinformatics stream at the Data Analytics Group. He has published 55 papers with high quality, including 7 papers in the flagship Bioinformatics journal. CI Le has secured over $1 millions of funding as a lead/sole CI including the NHMRC Early Career Fellowship (2017­2019) and DECRA (2020­2022). He has supervised 3 PhD students to completion and the principal supervisor of 4 current PhD students. He has also supervised two postdoc fellows, as well as 15 visiting master/PhD students.

Dr. Yanchang Zhao is a Senior Research Scientist with Data61, CSIRO (since 2017) and an Adjunct Professor with the University of Canberra (since 2015). Previously, he was a Data Analytics Lead with IBM Australia in 2017, a Senior Data Scientist with the Australian Government from 2009 to 2016 and an Australian Postdoctoral Research Fellow ¿ Industry (APDI) with the University of Technology Sydney (UTS) from 2007 to 2009. He received his PhD degree in Computing Science at UTS in 2007, specialised in data mining and machine learning.

He has 16 years' hands­ on experiences in data science and analytics and has authored/co­-authored 70+ publications (incl. 4 books) on data mining research and applications. He has delivered dozens of talks (incl. keynote addresses, invited talks, tutorials and training courses) at universities, government, industry and international conferences. His book titled R and Data Mining, Examples and Case Studies has been widely used as a reference book for university courses and industry training courses on data science and analytics.

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 $46,653 per annum (2023 rates). 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 $39,700 per annum (2023 rates).  

Eligibility and Selection 

This project is open to application from both domestic applicants, and international applicants onshore in Australia.

Applicants must meet the eligibility criteria for entrance into a PhD. Additionally applicants must meet the projects selection criteria: 

Essential:
  • Strong background in Statistics and Computer Science (Data Science)
  • Strong programming skills
Applicant who can also demonstrate the following will be highly regarded:
  • Having industry experience is a plus
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 Tuesday, 20th December.

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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