Fully funded PhD position in AI-Driven Optimisation for Electrified Transport Fleets - available from 2026/2027

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This project will develop a framework to optimise the schedule and operation of electrified transportation fleets. It will predict batteries performance, detect anomalies in real time, manage schedule uncertainties, adapt to battery health, charger availability and unexpected delays. Expected outcomes include improved reliability and efficiency, extended battery life and reduced operational costs. 

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Scholarship: 3.5 years at A$39,206 per annum.  International candidates will receive a tuition fee scholarship.

 

About you:

• First-class Honours/Masters (or equivalent) in Electrical/Computer Engineering, Computer Science, Applied Maths or related.

• Strong skills in AI techniques/ML/optimisation (Python/Matlab); familiarity with probabilistic modelling, time-series or control/power systems.

• Experience with batteries, EV/aviation systems, stochastic/robust optimisation, or IGDT.

 

How to apply:

• Send 1) CV, 2) transcripts, 3) a statement addressing fit and your most relevant project(s) to b.hredzak@unsw.edu.au with subject “PhD – AI Fleet Optimisation”.

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Applications reviewed on a rolling basis until filled.