Research Fellow (Digital Twin of Data Center)

Job Description

This project aims to develop intelligent control and digital-twin methods for energy-efficient data center thermal management. The work will involve modeling and simulation of data center cooling systems, together with the development of advanced control strategies. The candidate will use operational data, computational modeling, and optimization techniques to improve cooling energy efficiency, thermal reliability, and control robustness under dynamic IT workloads and environmental conditions.

Qualifications

• PhD degree in mechanical engineering, control engineering, energy systems, or a related field.
• Strong background in thermal-fluid systems, data center cooling, digital twins, and intelligent control.
• Experience in Python/MATLAB, numerical simulation, and data-driven modeling.
• Experience in model predictive control or reinforcement learning is preferred.
• Good publication record in energy-efficient cooling or AI-assisted energy systems is desirable.