Research Fellow (Transportation Engineering)

Responsibilities

• Integrate and manage multi-source transport datasets, including traffic flow, telematics, road geometry, signal timing, and incident records.
• Design and conduct simulation experiments to evaluate proposed safety interventions and quantify their impacts.
• Translate analytical outputs into actionable insights and decision-support tools for road safety management.
• Contribute to the development of a GIS-based platform for visualization, monitoring, and policy support.
• Prepare technical reports, research publications, and project documentation.
• Job Requirements:
• PhD degree in transportation engineering or related field
• Expertise in data analytics and computer programming
• Knowledge in traffic safety, urban transportation studies, traffic flow theory, operation research
• Proficiency in English - essential for data analysis and communication with stakeholders
• We regret to inform that only shortlisted candidates will be notified.
• Hiring Institution: NTU

Additional Information

The School of Civil and Environmental Engineering (CEE) at Nanyang Technological University, is a leading school for Sustainable Built Environment. The school plays an integral role in spearheading tertiary education, advancing research innovations and providing professional services in a number of key disciplines in Civil and Environmental Engineering and Maritime Studies fields, with the objective of contributing to the technological and economic advancement of Singapore and beyond. The school's mission in research is to achieve excellence by providing a conducive and intellectually stimulating environment to enable high quality work in strategic directions that are of significant impact to industry, science and technology. The Research Fellow will contribute to the development of an AI-assisted, data-driven road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and supporting the design of evidence-based interventions within a unified GIS-enabled decision-support platform.

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