Dynamic Behaviour and Engineering Optimisation of PEM Water Electrolysers under Real-World Conditions with AI Support
About the Project
Green hydrogen is widely recognised as a cornerstone of the global transition toward net-zero carbon emissions by 2050, owing to its clean energy potential. A critical determinant of its widespread adoption is the engineering of reliable, efficient, and durable water electrolysers, which convert water into hydrogen via electrochemical splitting. Yet, electrolyser systems face significant challenges: their operation is inherently dynamic, governed by fluctuating renewable energy inputs, intricate physico-chemical processes, and gradual degradation pathways. These factors hinder consistent efficiency, long-term stability, and cost-effectiveness, underscoring the need for advanced engineering solutions to overcome such limitations.
This PhD project is centred on the design, operation, and optimisation of proton exchange membrane (PEM) water electrolysers, with an emphasis on understanding their transient and steady-state behaviours under realistic operating conditions. Key research areas may include:
- Detailed characterisation of system responses under variable load profiles.
- Engineering strategies to mitigate degradation and extend component lifetimes.
- Optimisation of single- and multi-stack configurations to improve scalability and efficiency.
- Integration of physio-chemical and electrochemical insights into advanced design frameworks.
To complement this engineering focus, artificial intelligence (AI) and machine learning (ML) techniques will serve as enabling tools to accelerate discovery, prediction, and optimisation. Data-driven models will be employed for predictive failure analysis, real-time performance monitoring, and proactive maintenance planning. By combining rigorous experimental and engineering insights with AI-driven modelling, the project aims to deliver robust predictive tools and design guidelines that enhance stability, reduce costs, and enable the next generation of PEM electrolysers.
Ultimately, this research will contribute to lowering the levelised cost of green hydrogen and accelerating its integration into sustainable energy systems worldwide.
Candidates are required to have the following:
- First class in an Engineering/Science degree, preferably in Chemical Engineering/Physics/Chemistry
- Strong command of written and oral English
- Strong interest in water electrolysis and green technology development
- Knowledge of utilising machine learning tools will be an added advantage
- Possess good impact scholarly publications (eg: first author in a high-impact peer-reviewed journal article)
- Able to perform independent research and be a team player
Interested candidates who satisfy the criteria above should provide the following to Prof Chong Meng Nan (Chong.Meng.Nan@monash.edu) in their application:
- A 1-page cover letter that outlines your skills and experience
- CV which includes your education background and your publication record (if any)
- Evidence of English proficiency test (if any) (eg: IELTS, TOEFL)
How To Apply
It is suggested that you first contact the main supervisor and provide them with your academic background and achievements to determine whether you are a 'fit' for this research topic. If you feel you are a 'fit', please click here to complete an Expression of Interest, including your research proposal relevant to this project. Your EoI will be assessed and if you are eligible you will be invited to apply for PhD candidature and may be selected to interview for the scholarship
IMPORTANT: Starting May 2026, the Expression of Interest process described above will no longer apply. Updated application instructions will be available on this page from 4 May 2026.
Funding Notes
This project is funded by Monash University Malaysia. Successful PhD candidates will be paid a stipend with fully-funded tuition fees.
Find Your Best Opportunity
Tell them AcademicJobs.com sent you!