Research Fellow (Traffic safety and data analytics)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Traffic-safety-and-data-analytics%29/32493-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

A few Research Fellows (RFs) will be engaged in a research project to develop a robust, data-driven, and AI-powered framework for evaluating the impact of vehicle speed management policies, with a particular focus on age-related vulnerability. The proposed approach will explicitly account for the age profiles of road users, multiple vehicle types (e.g., passenger cars, trucks, and buses), as well as roadway and environmental conditions.The project aims not only to deepen the understanding of how age and vehicle speed jointly influence crash frequency and injury severity, but also to deliver practical tools to support the design of inclusive and adaptive speed management policies for an ageing population. In addition to utilizing road crash data, the project will also collect and incorporate driving simulator data to support model development and validation.

The selected RF will be required to collaborate closely with project team members on a range of activities:

. Traffic safety related data collection such as large-scale driving simulator experiments
. AI-based traffic safety modelling and analysis,
. preparation of technical reports and slides,
. engagement with stakeholders through meetings and discussions.

Job Requirements

. Possess a PhD in Traffic Safety, Computer Engineering/Science, Data Science related subjects (incl. PhD to be received in 6 months after starting work).
. Experience in developing driving simulator-based models.
. Ability to sophisticatedly use at least one programming language, e.g., Python, R Java, SQL, Julia, C# and C++.
. Excellent interpersonal and communication skills.
. Good teamwork and leadership, self-manage and motivated, with minimum supervision.
. Open to fixed-term contract.

Prioritized Requirements:

• driving simulator-based model development, machine learning skills.
• Research experience on traffic safety and driving simulator usage.
• Good publication record in international leading journals.