The Macquarie Variational Learning PhD funds research on variational decentralised learning in Australia. The official host is Macquarie University’s AI research environment. Applications close on 31 October 2026.
The award combines tuition support with a living allowance for a direct-entry three-year PhD. Domestic and international candidates can be considered. Strong mathematical foundations, programming ability and quality research outputs are essential.
Macquarie Variational Learning PhD Details
The table below summarises the current official opportunity, including its study or work route and application timing.
Use these details to identify the correct programme before applying. The official page linked at the end contains the controlling conditions and any later notices.
Host | Macquarie University |
|---|---|
Field | Variational decentralised learning; information technologies |
Study | Direct-entry 3-year PhD |
Support | Tuition fee offset/scholarship plus stipend |
Stipend | A$39,700 annually, full-time and indexed |
Deadline | 31 October 2026 |
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Macquarie Variational Learning PhD Benefits
The project combines variational, decentralised and deep learning to address local and global learning requirements. Its research includes distributional differences, uncertainty and decentralised non-IID data.
Funding has a tuition component and a separate living allowance. The official page describes the stipend as indexed; it does not establish a fixed net payment after every personal expense.
For a separate opportunity, review Macquarie Graph Modelling Scholarship. Its funding and eligibility conditions differ, so compare the individual guide before deciding.
Macquarie Variational Learning PhD Eligibility
Candidates need foundations in statistics, information theory and optimisation. The official description also requires programming skills and demonstrated research outputs.
This is a direct-entry doctoral award, not an introductory machine-learning course. The university explicitly says candidates without solid foundations and demonstrated outputs are ineligible.
Requirements and Documents
The initial expression of interest should contain selected publications and a CV. Include other evidence of your research foundations and achievements.
Make the relevance of each publication clear instead of supplying an unexplained list. Distinguish your own contribution to joint work and identify the methods you can use in the proposed research.
Other current guides include MBZUAI Postgraduate Scholarships and Hong Kong PhD Fellowship Scheme. Check their own subject, nationality and application requirements independently.
How to Apply
Before submitting the university application, send an expression of interest to Professor Longbing Cao. The official contact is longbing.cao@mq.edu.au.
Use the project-specific route and avoid describing the opportunity as a Griffith scholarship. Its official host, supervisor contact and research setting are all Macquarie.
Application Deadline
Applications close on 31 October 2026. The checked project page does not state an exact cutoff hour or timezone.
An expression of interest is required before formal submission. Allow time for the research-fit discussion; sending an EOI is not the same as receiving a scholarship offer.
Frequently Asked Questions
These answers address the main conditions that can affect whether this opportunity fits your plans.
They reflect the checked official information. Use the programme’s own application instructions for any requirement specific to your circumstances.
Is this hosted by Griffith University?
No. The official scholarship page and supervisor email identify Macquarie University.
Can international candidates apply?
Yes. The page lists domestic and international eligibility, subject to PhD entry and project requirements.
Are research outputs optional?
No. The official description requires demonstrated research outputs and solid foundations.
Conclusion
The Macquarie Variational Learning PhD is worth considering when its published conditions match your qualifications and plans. Prepare the application around the specific academic or professional requirements described above. Use the confirmed deadline state rather than a date copied from an older intake.
Before submitting, review the official programme information and check the current application instructions. Keep your supporting evidence consistent and retain the submission confirmation. Any selection or funding decision must come from the programme itself.
