job description
Join Nanyang Technological University (NTU), a global leader in engineering and technology research, as a Research Fellow in Power Engineering and Machine Learning. This is a unique opportunity to contribute to groundbreaking research in Digital Twin solutions for Li-ion batteries, shaping the future of energy storage and smart grid technologies.
In this role, you will collaborate with a multidisciplinary team of engineers, data scientists, and industry experts to develop AI-driven predictive models that enhance battery performance, safety, and longevity. Your work will directly impact sustainable energy solutions, supporting NTU’s mission to advance innovation in clean technology.
Based in Singapore, a global hub for research and development, you will have access to state-of-the-art facilities, cutting-edge resources, and a vibrant academic community. This position offers a competitive salary, professional growth, and the chance to publish high-impact research in top-tier journals.
Responsibility
- Design, develop, and validate Digital Twin models for Li-ion battery systems using machine learning and physics-based simulations.
- Conduct experimental and computational research to optimize battery performance, degradation prediction, and thermal management.
- Collaborate with cross-functional teams to integrate AI/ML algorithms into real-time monitoring and control systems.
- Publish research findings in high-impact journals and present at international conferences.
- Develop and implement data pipelines for battery health diagnostics and predictive maintenance.
- Support the supervision of graduate students and junior researchers in related projects.
- Stay abreast of emerging trends in power engineering, energy storage, and AI applications.
- Contribute to grant proposals and secure funding for future research initiatives.
Qualifications
- PhD in Electrical Engineering, Power Systems, Mechanical Engineering, Computer Science, or a related field with a focus on battery systems, machine learning, or Digital Twin technologies.
- Proven experience in Li-ion battery modeling, simulation, or experimental validation (e.g., using COMSOL, MATLAB, Python, or TensorFlow).
- Strong programming skills in Python, C++, or MATLAB for data analysis and algorithm development.
- Familiarity with machine learning frameworks (e.g., PyTorch, scikit-learn) and their application to energy systems.
- Experience with IoT, edge computing, or real-time control systems for battery management.
- Excellent analytical, problem-solving, and communication skills.
- Publication record in peer-reviewed journals or conferences on relevant topics.
- Ability to work independently and collaboratively in a fast-paced research environment.