Current open opportunities:

PhD opportunity:

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We are looking for an excellent candidate for a Ph.D. position in the Graph Research Lab (, School of Computing at the Australian National University. You will work under the supervision of Associate Professor Qing Wang, Dr Muhammad Farhan, Dr Henning Koehler and Professor Brendan McKay. You will be involved in developing new techniques and theory to advance state-of-the-art research in the area of graph algorithms, graph theory, and network science.

The ideal candidate should have

  • a Bachelor/Master’s degree in computing or mathematics with first-class honours or equivalent
  • a very good background in algorithms and theoretical computer science
  • excellent programming skills in C/C++/Java

Please email your inquiries/applications to Dr. Muhammad Farhan ( with the subject ‘PhD Application’ and the following documents:

  1. Cover letter and/or essay
  2. Resume
  3. Academic transcripts
  4. Prior research work (thesis/research papers etc.)
  5. Contact details of 2-3 referees


ARC Discovery Project PhD opportunities: “Deep Learning for Graphs”

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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.

Scholarship information

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)

  • A Bachelor/Masters degree in computing or mathematics with first-class honours or equivalent;
  • Excellent programming skills;
  • Strong interest in mathematics or theoretical computer science;
  • Good knowledge of machine learning/deep learning (e.g., have undertaken courses in machine learning).


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 ( with the subject ‘PhD Application’ and the following documents:

  1. You need to attach a motivation letter (max one page) on why you would like to join our team and about your research interests.
  2. Please also attach a CV, academic transcripts, previous research work, e.g., Honors/Masters thesis, papers, etc. There is no need to send certificates.
  3. Please indicate whether you are in Australia (on-shore) or outside of Australia (off-shore). Also, please indicate your country of citizenship.

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.


Data61 PhD opportunities: “Privacy-Enhanced Analytics on Evolving Graphs” (closed)

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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.

Skills/Capability required

  • Bachelor’s degree in Computer Science or relevant field.
  • Strong mathematical knowledge, knowledgeable in graph theory and/or machine learning techniques.
  • Some experience with programming languages (e.g. Python, R) and Privacy-Enhancing Technologies.

If you have any inquiries, please email them to Dr Thilina Ranbaduge (Data61, Black Mountain): ( or A/Prof. Qing Wang ( For the details on eligibility and how to apply, please visit the following link: