Leveraging Big Data and AI/ML for Smart Transport Solutions

Overview

This PhD position aims to harness the potential of big traffic and mobility data alongside cutting-edge AI/ML algorithms to pioneer innovative solutions for optimizing smart motorways and/or arterial traffic flow. By leveraging these technologies, the project endeavours to develop and test smart algorithms, with the goal of significantly enhancing the efficiency and safety of road networks.

Send via email to Prof. Ashish Bhaskar (ashish.bhaskar@qut.edu.au):

• a brief statement detailing your suitability for the position
• a detailed curriculum vitae, including a list of publications, if any
• contact details of two referees.

Selected applicants will be invited for an online zoom interview.

Research activities

• You will be working in close collaboration with the Industry (Department of Transport and Main Roads) and QUT Centre for Data Science.

Outcomes

• Highly applied research in collaboration with industry.
• Quality journal publications.

Skills and experience

• Honours undergraduate degree and/or a Master’s Degree in Data Science, Computer Science, Operational Research, Transport Engineering, or related fields.
• Evidence of experience in programming and data analytics.
• Research experience relevant to transport engineering or related fields.
• Self-motivated with the ability to work independently as well as in a team.
• Excellent written and verbal communication skills.

Scholarships

You may be eligible to apply for a research scholarship.

Explore our research scholarships

Keywords

• smart transport
• Data science in transport
• smart mobility
• AI and ML in transport

Contact

Contact the supervisor for more information.