PhD scholarship in advancing stochastic optimisation

PhD scholarship in advancing stochastic optimisation

The PhD scholarship includes a PhD stipend funded by the ARC Discovery Project DP260104880, Advancing stochastic optimisation: highly-correlated restless bandit models, and a tuition fee scholarship offered by RMIT SGR.

RMIT University is seeking a highly motivated PhD candidate to work on the project "Advancing stochastic optimisation: highly-correlated restless bandit models", funded by the Australian Research Council (ARC) Discovery Project DP260104880. The project will be based in the School of Engineering at RMIT's Melbourne City campus.

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$35,886 per annum (indexed in line with centrally awarded scholarships) + a tuition fee scholarship (tuition fee waiver)

One (1).

Please check the minimum requirements for admission to a Doctor of Philosophy (PhD) at How to apply. 

2029-03-01

Please contact Dr Jing Fu (jing.fu@rmit.edu.au) by 30th of April, 2026, with: 1. A brief cover letter explaining your interest in the project and your relevant experience 2. Your CV (including any publications, if applicable) 3. Academic transcripts (official or unofficial) Shortlisted applicants will be invited to submit your EOI through PhD (Electrical & Electronic Engineering) - Apply.

The prospective HDR student is expected to have fundamental knowledge of stochastic modeling (such as Markov decision process), probability, reinforcement learning, and linear/convex optimization, and good programming skills for large-scale simulations. Python experience is required.

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