What you'll receive
31 January 2024
If you're an international student, you will also receive a tuition fee sponsorship for your research degree.
As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research in and across the field.Eligibility
To be eligible you must:
The first step is to email Associate Professor Ting Liao detailing your academic and research background, your motivation to research in this field and interest in this scholarship, and include your CV.What happens next?
If supported to apply, you will then submit an Expression of Interest (EOI) following the advice at How to apply for a research degree.
In your EOI, nominate Associate Professor Ting Liao as your proposed principal supervisor, and copy the link to this scholarship into question 2 of the financial details section.About the scholarship
The scholarship is available as part of Associate Professor Ting Liao’s ARC Discovery Project within the School of Mechanical, Medical and Process Engineering and supported by the Centre for Materials Science. The project is supported by a top-up scholarship and travel funding.
The successful candidate will become part of Low Dimensional Sustainable Energy research group. Our research group is a transdisciplinary space that combining experimental and theoretical expertise on co-designing low dimensional materials for sustainable energy applications. The candidate will be supervised by Associate Professor Ting Liao and have the opportunity to engage in a dynamic environment with members of the School of Mechanical, Medical and Process Engineering and Centre for Materials Science.
This PhD or Master project aims to design multifunctional single atom catalysts on two-dimensional support with optimized electronic coupling states, favourable SACs coverage, and charge transfer performance, and to modulate the stability and overall catalytic properties by engineering support surface modifications and coverage on the nanoscale to meet the requirements of sustainable energy conversion and storage applications, using state of-the- art Density Functional Theory based computational approaches.