Research Fellow (Transportation Engineering/ Computer Engineering/Science)

NANYANG TECHNOLOGICAL UNIVERSITY; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A prestigious educational institution in Singapore is seeking a Research Fellow to focus on safety assessment and accident prediction models using AI technology for mixed-traffic environments. The role includes designing driving simulations, developing deep learning models, and analyzing traffic data. A Ph.D. by December 2025 in a relevant field is required. Strong programming skills in Python and a background in AI are essential. This position offers an opportunity to contribute to Singapore's transition to safer traffic systems.

Qualifications

• Ph.D. degree in a related discipline by December 2025.
• Expertise in AI, deep learning, and programming.
• Experience in driving simulation or traffic safety analysis.

Responsibilities

• Design and conduct driving simulation experiments for risk assessment.
• Develop deep learning models for safety assessment.
• Process and analyze multi-source traffic data.

Skills

AI

Deep learning

Python

Data analysis

Teamwork

Education

Ph.D. in transportation engineering or related discipline

Tools

PyTorch

Job description

School of Civil & Environmental Engineering (CEE@NTU)

CEE 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.

We are looking for a research fellow (RF) who shall research into safety assessment and accident prediction models using AI technology for mixed-traffic environments.

Key Job purpose

Research into safety assessment and accident prediction models using AI technology for mixed-traffic environments. Insights shall be distilled into clear, evidence-based recommendations to guide Singapore’s transition toward a safer, more efficient, and sustainable mixed-traffic future.

Key Responsibilities

• Design and conduct driving simulation experiments for risk scenario analysis.
• Develop deep learning models, such as GNNs and TCNs, for safety assessment and accident prediction.
• Process and analyse multi-source traffic data for model training and validation.
• Publish technical findings in top-tier journals.

Job Requirements

• A Ph.D. degree in a related discipline (transportation engineering, computer engineering/science, or related disciplines) by December 2025.
• Expertise in AI, deep learning, and programming (e.g., Python, PyTorch).
• Practical experience in at least one of: driving simulation, spatiotemporal AI models, or traffic safety analysis.
• Strong publication record is an advantage.
• Excellent English communication - essential for data analysis and communication with stakeholders
• Strong teamwork under deadlines; grant writing experience is a plus

We regret to inform that only shortlisted candidates will be notified.