MUM
Dynamic Behaviour and Engineering Optimisation of PEM Water Electrolysers under Real-World Conditions with AI Support
✓ Fully Funded
🎓 Artificial Intelligence
🎓 Chemical Engineering
🎓 Data Science
🎓 Energy Technologies
🎓 Fluid Mechanics
🎓 Machine Learning
🎓 Materials Science
🎓 Mechanical Engineering
machine learning
renewable energy
Malaysia PhD
green hydrogen
PEM electrolyser
electrochemical systems
predictive maintenance
water electrolysis
Funded PhD at Monash University Malaysia focused on PEM water electrolysers, combining engineering and AI to improve hydrogen production under real-world operating conditions.
Project Description
This PhD project investigates the dynamic behaviour and engineering optimisation of proton exchange membrane (PEM) water electrolysers for green hydrogen production.
The research focuses on improving the reliability, efficiency, and durability of electrolyser systems operating under realistic conditions influenced by variable renewable energy inputs and long-term degradation.
Key research areas include:
Characterisation of system response under variable load profiles
Engineering strategies to reduce degradation and extend component life
Optimisation of single-stack and multi-stack electrolyser configurations
Integration of physico-chemical and electrochemical insights into design frameworks
Use of AI and machine learning for prediction and optimisation
AI and machine learning will be used to support:
Predictive failure analysis
Real-time performance monitoring
Proactive maintenance planning
Data-driven optimisation of electrolyser systems
The project combines experimental engineering research with data-driven modelling to support the development of more stable and cost-effective green hydrogen systems.
Entry Requirements
First Class degree in Engineering or Science, preferably Chemical Engineering, Physics, Chemistry, or related field
Strong written and spoken English
Preferred:
Interest in water electrolysis and green technology
Knowledge of machine learning tools
Strong research background and publications
Candidate should be able to work independently and as part of a team.
Strong written and spoken English
Preferred:
Interest in water electrolysis and green technology
Knowledge of machine learning tools
Strong research background and publications
Candidate should be able to work independently and as part of a team.
How to Apply
Contact the supervisor (Prof Meng Nan Chong)
Submit:
1-page cover letter
CV including education and publication record
English proficiency evidence if available
Submit Expression of Interest (EoI) with research proposal
If shortlisted, proceed to application and interview
Note:
Process changes from May 2026
Check updated instructions from 4 May 2026
Submit:
1-page cover letter
CV including education and publication record
English proficiency evidence if available
Submit Expression of Interest (EoI) with research proposal
If shortlisted, proceed to application and interview
Note:
Process changes from May 2026
Check updated instructions from 4 May 2026
Eligibility
UK/Home
EU
International
Supervisor Profile
PM
Prof Meng Nan Chong, Dr Joshua Zheyan Soo, Dr Chin Vern Yeoh
Monash University Malaysia, Engineering and Information Technology
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