job description
Join Nanyang Technological University in a groundbreaking role as a Research Associate in Power Engineering and Machine Learning, based in the vibrant hub of Denpasar, Bali. This position offers a unique opportunity to contribute to cutting-edge research in lithium-ion battery modeling, state estimation, and wireless charging optimization—key technologies driving the future of green energy and sustainable power systems.
As part of a dynamic, interdisciplinary team, you will leverage advanced machine learning algorithms and power electronics principles to develop innovative solutions for energy storage, efficiency, and smart grid integration. Your work will directly impact the global transition toward cleaner, more reliable energy infrastructure, aligning with NTU’s mission to pioneer technological advancements for a sustainable world.
This role is ideal for a motivated researcher with a passion for renewable energy, AI-driven optimization, and power systems engineering. You’ll collaborate with leading academics and industry partners, publish high-impact research, and contribute to real-world applications that shape the future of energy technology.
Responsibility
- Develop and validate high-fidelity lithium-ion battery models using data-driven and physics-based approaches.
- Design and implement state-of-charge (SOC) and state-of-health (SOH) estimation algorithms for battery management systems.
- Optimize wireless power transfer systems for electric vehicles and portable devices using machine learning.
- Conduct experimental testing and simulation studies to evaluate performance, efficiency, and safety of energy storage systems.
- Collaborate with cross-functional teams to integrate ML models into real-time control systems for smart grids and microgrids.
- Publish research findings in peer-reviewed journals and present at international conferences.
- Contribute to grant proposals and secure funding for sustainable energy research projects.
- Mentor junior researchers and students in advanced power engineering and AI methodologies.
Qualifications
- PhD or Master’s degree in Electrical Engineering, Power Electronics, Energy Systems, or a related field with a focus on machine learning applications.
- Proven experience in battery modeling, state estimation, or power system optimization (academic or industry).
- Proficiency in Python, MATLAB/Simulink, or C++ for algorithm development and simulation.
- Strong background in machine learning frameworks (e.g., TensorFlow, PyTorch) and data analysis tools.
- Familiarity with power electronics, control systems, and embedded programming (e.g., Arduino, Raspberry Pi).
- Experience with wireless power transfer, EV charging, or renewable energy integration is a plus.
- Excellent analytical, problem-solving, and communication skills for technical and non-technical audiences.
- Ability to work independently and collaboratively in a fast-paced research environment.