PhD in Interpretable Machine Learning for Sustainable Lithium-Ion Battery Recycling Curtin University in Australia

PhD opportunity at Curtin University in Interpretable Machine Learning for Sustainable Lithium-Ion Battery Recycling.

This project focuses on the separation and purification of spent lithium-ion battery electrodes using a combination of hydrometallurgy, machine learning, and explainable AI (XAI). The research aims to improve recovery of critical metals such as Li, Ni, Co, and Mn, while reducing chemical consumption, waste generation, and process costs.

The project is highly interdisciplinary and is suitable for applicants interested in chemical engineering, metallurgical engineering, materials science, mineral processing, environmental engineering, data science, and related fields. The work includes experimental hydrometallurgical processing, advanced materials characterization, predictive modelling, and interpretable machine learning methods such as SHAP, feature importance, and sensitivity analysis.

Preferred applicants should have a Bachelor Honours or Master degree in a relevant discipline, plus interest or experience in laboratory work, analytical techniques, programming, and data analysis. The project is open to both international and domestic applicants, and candidates must meet the entry requirements for a PhD at Curtin University.

Funding is not fully specified in the post, but the preferred candidate may be considered for an RTP scholarship. The project also mentions possible internship and industry engagement opportunities depending on progress and partner availability.

How to apply: contact Dr Lisha Dong for enquiries and submit an Expression of Interest during the Central Scholarship round (1 July–31 July 2026).