Established in 2010, the Energy Research Institute @ NTU (ERI@N) is a pan-university research institute that focuses on systems-level research for tropical megacities. It performs translational research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology deployment enabling validation and demonstration of real-world applications.

For more details, please view https://www.ntu.edu.sg/erian

We are looking for experienced individuals with a strong background in computational modelling, thermal energy systems, and machine learning. The hired researchers will join an interdisciplinary team to develop innovative integrations of advanced computational techniques and thermal energy storage solutions, focusing on discovering novel materials and optimizing energy systems through machine learning. Promising solutions developed will be experimentally validated, demonstrated and potentially commercialised at ERI@N.

Key Responsibilities:

• Work closely with colleagues to ensure the requirements of the research project are met
• Conduct computational fluid dynamics (CFD), molecular dynamics (MD), and/or density function theory (DFT) studies for energy material development
• Use artificial intelligence (AI) techniques for material discovery and/or device design
• Use 3D printing techniques to fabricate phase change materials (PCM) composites
• Assist in experimental works or other required works by the PI
• Use data science techniques to process experimental results
• Write scientific papers/technology/reports and other work-related documents
• Develop machine learning algorithms for material discovery and novel heat exchanger design to seamlessly integrate PCMs into thermal systems.
• Fabricate PCM composites with optimized geometries through 3D printing technologies.

Job Requirements:

• Master's degree in Material Science, Chemistry, Mechanical Engineering, Chemical Engineering, Mathematics, or equivalent disciplines from a prestigious university
• At least 1 year of research experience with python, Matlab, or C++
• Experience in CFD/DFT/MD is preferable
• Experience in machine learning is preferable
• Experience in thermal energy storage, hydrogen, and energy systems is preferable

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU