PhD in Data-Driven Modelling for Low-Carbon Industrial Energy Systems Monash University Malaysia in Malaysia

This PhD opportunity at Monash University Malaysia focuses on the development of advanced data-driven modelling approaches for the design and optimisation of low-carbon industrial energy systems. The project aims to integrate process simulation, system-level analysis, and digital tools to evaluate and enhance the performance, efficiency, and operational reliability of emerging energy infrastructures in industrial applications. Research will explore how digitalisation and data science can support improved system integration, informed decision-making, and the scalability of sustainable energy solutions.

Students will work within the Department of Engineering and Information Technology, engaging with interdisciplinary research areas such as Data Science, Internet of Things, and Chemical Engineering. The outcomes of this research are expected to contribute significantly to the development of more sustainable and resilient industrial energy systems, addressing global challenges in energy efficiency and carbon reduction.

The position is supervised by Professor Chong Meng Nan, an expert in the field. The project is fully funded for students worldwide, offering both a living stipend and a tuition waiver under the GRES scheme. Applicants must hold a First Class Honours (H1) degree or its equivalent, as recognised by Monash University Malaysia, and meet the university’s English language requirements. Evidence of English proficiency (IELTS, TOEFL, or equivalent) is required if applicable.

To apply, candidates should first contact Prof Chong Meng Nan with their academic background and achievements to discuss suitability for the project. If a good fit is established, applicants should complete an Expression of Interest (EoI) via the provided link, including a research proposal relevant to the project. Eligible candidates will be invited to formally apply for PhD candidature and may be selected for a scholarship interview. Note that the application process will change after May 2026, with updated instructions available from 4 May 2026.

This is an excellent opportunity for highly qualified candidates interested in sustainable energy, digital modelling, and industrial innovation to pursue doctoral research at a leading international institution.