Supported by a grant from the Australian Research Council, we are currently looking for new PhD students with passion, talent and grit to join the team. You will have the chance to work on the grand challenges at the intersection of deep learning and graph theory. You will be involved in discussing important and interesting questions in this challenging area, developing new heuristic techniques and theories to advance state-of-the-art methodologies, and evaluating their applications in solving real-world problems. Each PhD student will have their own PhD project under the joint supervision of Prof. Brendan McKay and A/Prof. Qing Wang, and may collaborate on other related projects in the team.
Two PhD scholarships are available, each including a living allowance of $28,597 per annum with a waived tuition fee, in accordance with the standard of ANU University Research Scholarships. The successful applicants will be supported by the scholarship for 3.5 years.
Eligibility (please do not apply if these conditions are not met)
The following conditions are preferred but not compulsory: (1) have previously done some research work, particularly in the area of machine learning, and (2) have a good knowledge of graph theory or related subjects.
Please email your inquiries/applications to A/Prof. Qing Wang (email@example.com) with the subject ‘PhD Application’ and the following documents:
Please note that short-listed applicants for these PhD scholarships will need to apply for admission to a PhD program following the ANU HDR policy and meet the language requirements by ANU. We will provide you further information once you are selected.
There are some PhD opportunities with potential full scholarships available for those interested in research involving machine learning and data privacy. The application deadline is 5 November.
If you have any inquiries, please email them to Dr Thilina Ranbaduge (Data61, Black Mountain): (firstname.lastname@example.org) or A/Prof. Qing Wang (email@example.com). For the details on eligibility and how to apply, please visit the following link: