AI-Driven Road Safety Research Fellow (GIS/Analytics)

NANYANG TECHNOLOGICAL UNIVERSITY

Singapore

On-site

SGD 70,000 - 110,000

Full time

3 days ago
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Job summary

The School of Civil and Environmental Engineering at Nanyang Technological University invites a Research Fellow to develop an AI-assisted, data-driven road safety analytics framework. The role entails integrating multi-source transport datasets, building ML models for risk identification, and contributing to a unified GIS-enabled decision-support platform.

The successful candidate will have a PhD in transportation engineering or a related field, strong data analytics and programming skills, and

Qualifications

  • PhD degree in transportation engineering or related field.
  • Excellent analytical and programming skills.
  • Knowledge of traffic safety, urban transportation studies, traffic flow theory, and operations research.
  • Strong written and verbal communication skills.

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.

Skills

Data analytics
Computer programming
Traffic safety knowledge
Urban transportation studies
Traffic flow theory
Operations research
Strong communication

Education

PhD in transportation engineering or related field

Tools

GIS software

Job description

The School of Civil and Environmental Engineering at Nanyang Technological University invites a Research Fellow to develop an AI-assisted, data-driven road safety analytics framework. The role entails integrating multi-source transport datasets, building ML models for risk identification, and contributing to a unified GIS-enabled decision-support platform.

The successful candidate will have a PhD in transportation engineering or a related field, strong data analytics and programming skills, and

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