Research Fellow, Traffic Management Project

Jan 03, 2022
End of advertisement period
Feb 02, 2022
Contract Type
Full Time

Job Description

Applications are sought for a Postdoctoral Fellow to work on a Traffic Management Project. The project is primarily focused on applying data-driven analytics and simulation for Traffic Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters. This project is a National Research Foundation (NRF)/Australian Research Council (ARC) collaborative project between National University of Singapore (NUS), Nanyang Technological University (NTU), and several partners in Australia, namely Swinburne University of Technology (SUT), Melbourne, and University of Technology (UTS), Sydney. The appointed postdoc and research assistant will jointly work on the design and development of a data-driven traffic simulation model that combines data-driven and simulation-based techniques, so that it can support multi-level, multi-modal and on-demand traffic simulation.


Knowledge, Skills and Abilities

  • Postdoctoral candidates should have a Ph.D in Traffic Engineering/Computer Science or related degree, and be familiar with
    • Data modelling and collection
    • Traffic Systems
    • Traffic Modelling and simulation
    • Agent-based systems & simulation
    • Experience in Human Behaviour models will be useful
  • Candidates should be proficient in C++, Python, and preferably have experience with Traffic Simulation models or packages.

Personal Attributes

  • Proficient in English (speaking and writing)
  • Independent and highly motivated
  • Good interpersonal communications
  • Able to work in a team

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