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University of Melbourne

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University of Melbourne PhD Scholarship

Fully Funded PhD in Strategy Extraction and Generalisation for AI Agents University of Melbourne in Australia

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded 3.5-year PhD scholarship. Available for both domestic and international candidates.

Deadline

Nov 20, 2026

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Country

Australia

University

University of Melbourne

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Keywords

Computer Science
Information Technology
Mathematics
Artificial Intelligence
Ontology
Generalizability
Statistics
ML

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About this position

Fully funded 3.5-year PhD opportunity at the University of Melbourne, School of Computing and Information Systems, in Australia.

Research topic: Strategy extraction and generalisation for AI agents. The project focuses on developing new methods for AI agents to learn strategic knowledge from observed behaviour and transfer that knowledge to new tasks with different representations. The work builds on sequence alignment techniques, ontological reasoning, strategy transfer, and policy learning.

Research directions include:

- Minimising manual modelling of source and target task domains.
- Extracting more sophisticated strategies, including conditional, hierarchical, and temporally extended patterns.
- Finding strategically relevant similarities across contexts with substantially different representations.

Ideal background: computer science, mathematics, or a related field, with interest in machine learning, knowledge representation and reasoning, or sequential decision-making.

Funding: fully funded scholarship for 3.5 years, open to both domestic and international candidates.

Application: submit an expression of interest form plus a one-page CV and academic transcripts. Expressions of interest close on 20 November 2026 for an early 2027 start.

Supervisor/poster: Michelle Blom, Senior Lecturer.

Funding details

Fully funded 3.5-year PhD scholarship. Available for both domestic and international candidates.

What's required

Applicants should have a strong background in computer science, mathematics, or a related field, with interest in machine learning, knowledge representation and reasoning, or sequential decision-making. The post asks for a one-page CV and academic transcripts as part of the expression of interest.

How to apply

Complete the expression of interest form and submit a one-page CV and academic transcripts. Expressions of interest close on 20 November 2026 for an early 2027 start.

More information can be found here

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