Research Fellow – Swinburne’s Intelligent Data Analytics Lab
Applications close: 8 August 2021
Description: We are seeking a Research Fellow to undertake research in “Data-Driven Traffic Analytics and Simulation for Incident Analysis and Management”, supported by the ARC Linkage Funding Scheme. The Fellow will be positioned in the Department of Computer Science and Software Engineering located at the Hawthorn Campus, and work closely with Swinburne researchers in intelligent transport systems from the Department of Civil and Construction Engineering and also the external researchers from Data61, UTS, NTU (Singapore) and NUS (Singapore) who are the partners of the ARC Linkage Project.
The primary expectation of the position is to make original and innovative contributions to designing and developing (1) advanced machine learning techniques for traffic incident detection and classification and incident severity prediction and estimation, (2) a data-driven traffic simulation model that allows for multi-level, multi-modal and sub-network simulation, adaptive to dynamic and multi-modal traffic conditions, (3) multi-modal impact analysis techniques for evaluating the impact of an incident on the multi-modal traffic network, and (4) interactive multi-objective optimisation techniques to create appropriate response plans to mitigate incidents. The Fellow will also contribute to implement and evaluate a proof-of-concept system.