job description
Are you passionate about pushing the boundaries of thermal management and AI-driven infrastructure? The National University of Singapore (NUS) is seeking a highly motivated Research Fellow to join our innovative team focused on the development of a Digital Twin for Data Centers.
As the global demand for cloud computing and AI escalates, data centers face unprecedented energy consumption challenges. In this role, you will contribute to a cutting-edge project aimed at developing intelligent control strategies and high-fidelity digital twin models. You will translate complex data into actionable thermal management solutions, driving energy efficiency and operational sustainability. This is a unique opportunity to conduct high-impact research in one of the world's top academic institutions, working alongside leading experts in mechanical, electrical, and systems engineering.
The ideal candidate will bridge the gap between theoretical modeling and practical implementation, utilizing advanced simulation tools and machine learning techniques to optimize data center environments.
Responsibility
- Develop and refine digital twin frameworks for data center thermal modeling and energy analysis.
- Design intelligent control algorithms to optimize cooling systems based on real-time sensor data.
- Conduct high-fidelity simulations to predict thermal performance under varying workload scenarios.
- Collaborate with interdisciplinary teams to integrate IoT sensor networks and data acquisition systems.
- Analyze complex data sets to identify efficiency gaps and propose innovative mitigation strategies.
- Document research findings, prepare technical reports, and contribute to high-impact academic publications.
- Mentor junior researchers and assist in the management of project-related laboratory equipment.
Qualifications
- PhD in Mechanical Engineering, Electrical Engineering, Computer Science, or a closely related field.
- Proven research experience in thermal management, HVAC systems, or data center operations.
- Strong proficiency in programming languages such as Python, MATLAB, or C++.
- Experience with simulation software (e.g., Ansys Fluent, OpenFOAM, or Modelica).
- Knowledge of machine learning, reinforcement learning, or control theory for complex systems.
- Strong analytical problem-solving skills and the ability to work independently.
- Excellent verbal and written communication skills in English.