PhD Studentship Opportunities in Boiler Optimisation Project (Industry Project) at Universiti Malaya

We are looking for two postgraduate students (PhD) to join our research project on boiler optimisation (fuel–combustion–digital twin-Reinforcement Learning integration), for March 2026 intake.

Project Overview

This is a collaborative R&D project with our industrial partner operating boilers for in-house power generation. At present, boiler operation is driven mainly from the steam side with limited visibility of what happens inside the furnace and how day-to-day fuel variations affect combustion efficiency. The project will combine fuel characterisation, combustion testing, CFD modelling and a data-driven digital twin of the boiler–turbine system. These models and measurements will be embedded into a custom decision-support and optimisation tool that recommends fuel- and condition-specific operating settings. The ultimate goal is to deliver a deployable prototype that helps operators run the boilers more efficiently.

Requirements

Position 1: Digital Twin & Reinforcement Learning

Scope

- Data collection at the boiler

- Develop a data-driven digital twin of a boiler–turbine system

- Implement and test reinforcement learning (RL) strategies for combustion and boiler efficiency optimisation

- Integrate plant data into the decision-support tool

Preferred background

- Master's in Mechanical / Chemical Engineering, Control / Mechatronics, Computer Science, or related field, with a CGPA above 3.5.

- Solid Python skills and experience with at least one ML framework (e.g. PyTorch, TensorFlow or similar)

- Interest in process systems, control, or optimization

- Experience with time-series modelling, digital twins, and RL

- Familiarity with power plant or energy systems data

Position 2: CFD Modelling of Combustion

Scope

- Data collection at the boiler

- Build and simulate 3D CFD models of a boiler (furnace + grate)

- Study combustion, flow, temperature, and slagging / fouling behaviour under different operating conditions

- Provide CFD-informed operating envelopes for the decision-support tool

Preferred background

- Master's in Mechanical / Chemical Engineering (thermos-fluids / combustion focus), with a CGPA above 3.5.

- Strong fundamentals in heat transfer, fluid mechanics and combustion

- Hands-on experience with CFD (ANSYS Fluent/ OpenFOAM.)

- Prior work in combustion CFD (flames, furnaces, burners, boilers, engines, etc.)

* Applicants with experience in writing scientific paper, and passionate and proactive in conducting research is preferred.

* Good communication and writing skills in English.

Funding

Candidates are expected to complete the PhD within two years.

- The scholarship will provide monthly stipends and a full waiver of Universiti Malaya tuition fees for the duration of the studentship.

- The PhD application fee and visa-related costs are not covered.

Application 

Please email your application to Dr Meor Faisal Zulkifli at [Confidential Information] with the following attachments: CV, GitHub link (optional),

academic transcripts, and certificates.

• Email subject: Application – Graduate Teaching Assistant (GRA) Opportunities in Boiler Optimisation – Your Name

• File names: YourName_CV.pdf, YourName_Transcript.pdf, YourName_Certificates.pdf