The Complex System Modeling and Optimization team develops advanced techniques to optimize complex systems for environmental and sustainability goals such as carbon neutrality. Our research, which is both experimental and theoretical, covers domains including data science, simulation and modeling, optimization and control, and has led to many publications in top conferences. Our research goal is to understand the complexity of real-world systems and build innovative solutions to drive the creation of social values such as carbon neutrality. We have built several analytic engines and system solutions to analyze big data and support various applications in system modeling and optimization.
We are looking for a talented, self-motivated researcher to create cutting-edge technologies. The ideal candidate must be able to research and analyze complex problems and develop data-oriented modelling and simulation for large scale systems. S/he must have a Bachelor’s degree or higher in Computer Science, Operations Research, Industrial Engineering, or other recognized engineering disciplines, with experience in at least one of the following areas:
• Artificial Intelligence, machine learning, and deep neural networks
• Complex system simulation
• Computational modeling and partial differential equations
• Large scale optimization and learning
• Automated system testing, debugging, and problem root cause analysis
• Signal processing, system identification, and control