PhD Scholarships (Next Generation Graduates Program): 1. An Internet of Things Platform for Screening Digital Twin; 2. AI-empowered Manufacturing Technologies for Screening Digital Twin

• Department of Engineering Technologies
• This position is currently located at the Hawthorn campus. The incumbent must be willing to travel between and work at a range of locations
• Stipend $41,650.00 (p.a.) for 3.5 years

About the Scholarship
Join the Next Generation Graduates Program, a cutting-edge cohort-based initiative aimed at fostering entrepreneurial thinking and multidisciplinary skills essential for driving innovation in AI and emerging technologies. As a participant, you'll engage with a diverse national cohort, preparing you for dynamic problem-based environments in your respective fields. This scholarship program, in collaboration with Swinburne University of Technology and industry leader Sandvik Rock Processing Australia, offers the opportunity to develop groundbreaking Digital Twin (DT) solutions empowered by Artificial Intelligence of Things (AIoT). By digitally representing physical objects and harnessing real-time IoT data, our goal is to enhance productivity and reduce maintenance costs for our industry partners.

Partnering with Sandvik, a global leader in the METS sector, we're focused on developing a screening digital twin capable of predicting material behaviours in processing plants. Through the integration of AI and data analytics, this innovative solution will adapt to changing real-world conditions, optimizing performance and revolutionizing the screening process. Don't miss this chance to be at the forefront of technological advancement and make a tangible impact on industry transformation. Apply now to join our pioneering program and shape the future of AI-driven innovation.

1. An Internet of Things (IoT) Platform for Screening Digital Twin: The PhD project #1 will develop an IoT platform by integrating the existing and newly built system sensors to construct a screening digital twin, capable of simulating parameter changes for screening performance and efficiency prediction. 

2. Artificial Intelligence (AI)-empowered Manufacturing Technologies for Screening Digital Twin: The PhD project #2 will develop new AI algorithms tailored for predicting material behaviours based on material parameters and real operating conditions.

To be eligible for the scholarship, applicants must be domestic students as per the Higher Education Support Act at the time of award. Domestic students include:
a. Australian citizens,
b. Australian permanent residents,
c. a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time; or
d. a New Zealand citizen.

About you 
To be successful in the role, you will:

• Meet Swinburne PhD admissions requirements. 
• Meet University language requirements.
• Must be domestic students.
• Be able to commence the program in the year of the offer. 
• Enrol as a full-time PhD student. 
• Have previous study in an appropriate area of Robotics & Mechatronics Engineering and/or Computer Science. 

A full list of selection criteria is available within the position description. 

About Swinburne University of Technology
Swinburne Horizon 2025 draws upon our understanding of future challenges. With this new strategic plan, we choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of Entrepreneurship, and proud of it. We are committed to a differentiated university proposition in education and research, so that:

• Every Swinburne learner gets a work experience
• Every Swinburne graduate gets a job
• Every Swinburne partner gets a tech solution
• Swinburne is the prototype of global best practice

The achievement of our 2025 moon shots depends on our capacity to work collectively, always, as One Swinburne.

How to apply and further information
Please submit your CV, academic transcripts, and cover letter addressing why you believe you are suitable for this position according to Key Selection Criteria.  

For further information about this position, contact Prof. Jiong Jin at [email protected]

Please Note: Appointment to this position is subject to passing a Working with Children Check.

If you are experiencing technical difficulties with your application, please contact the Swinburne Talent Acquisition Team on [email protected]  

Applications Close: Sunday 31st March 2024, at 11pm. 

Swinburne offers flexible working options, leave and parenting/carer policies to support work life balance.

Equity and Diversity 
Swinburne is a large and culturally diverse organisation and we are proud of our commitment to equity, diversity and inclusion through key initiatives.  For further information on all our initiatives visit our Equity & Diversity website .

We welcome and encourage applicants from diverse backgrounds to apply.

We are committed to making the recruitment process fair and equitable for all our candidates. If you have specific accessibility or support requirements please contact [email protected]

Aboriginal and Torres Strait Islander Applicants
We welcome and strongly encourage applications from Aboriginal and Torres Strait Islander people.  

For any support please contact [email protected] or for more information on our Indigenous strategies please follow the link to our RAP Reconciliation Action Plan

As a signatory to Victoria’s Commitment to Action , Swinburne seeks to remove barriers to international graduate employment. We welcome and encourage applications from international graduates.  

(Agency enquiries will not be accepted for this position)

(#LI-SW)

Click here for Position Description Opens in new window