NTU Main Campus, Singapore

School of Computer Science and Engineering (SCSE) is looking for highly motivated Research Fellow with strong research interest on applying advanced AI and machine learning techniques for mobility data completion, inference, mining, and generalization.

The research team has been deepening the understanding of mobility from heterogeneous spatiotemporal data and is making use of such understanding to develop intelligent methods and systems to improve state-of-the-art practices of transportations as well as other urban applications with a special focus on traffic or impact analysis.

Key Responsibilities:

• Conduct both independent and joint research on data analytics for wireless, mobile and urban transportation applications
• Apply advanced AI and machine learning techniques for mobility data completion, inference, mining, and generalization
• Work with high volumes of experimental data using distributed processing frameworks and advance graph processing engines

Job Requirements:

• PhD degree in Computer Science and Engineering or related fields
• Minimum 4 years of research experience in the field
• Strong research background in urban mobility and traffic analysis
• Strong experimental background in processing large transportation datasets and in building end-to-end urban mobility applications
• Knowledge in distributed data processing framework such as Sparks, GraphX
• Familiar with at least one deep learning framework such as TensorFlow, Torch, etc
• Strong track record of publishing in top venues on mobility, systems, transportation such as MobiCom, KDD, INFOCOM, UbiComp, MobiSys, etc

We regret that only shortlisted candidates will be notified.

Hiring Institution: NTU