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Job Description
This position involves working on a project related to traffic signal control at multiple intersections. The objective of this position includes contributing to the model development, solution and implementation of robust traffic signal control of the intersections using machine learning methods. The role involves the opportunity to work with the research team within National University of Singapore in which the team leaders are from the Department of Industrial Systems Engineering & Management, the Department of Mechanical Engineering, and Specialists from a high technology company. The successful candidate will be self-motivated with an outstanding track record in computer science, machine learning (in particular, reinforcement learning), or transportation and related disciplines.
The main research tasks for the project include but will not be limited to:
• Developing robust centralized and decentralized controllers for traffic signals, based on local sensing at the junction and communication among neighbouring junctions.
• Developing models that can optimize traffic flow, decrease wait time, but also improve pedestrian throughput throughout the system.
• Testing and optimizing the scalability of the devised controllers in city-wide simulation scenarios involving both vehicles and pedestrians, using a microscopic simulation software such as SUMO or VISSIM.
• Designing and implementing controllers on hardware to obtain a laboratory-level prototype system.
Qualifications
• PhD in Operations Research, Computer Science, Engineering, Transportation, or related subjects.
• Experience in developing/applying data-driven models in transportation or big-data related projects.
• Proficiency with GNU/Linux, Python/C++ and at least one of the main machine learning libraries (e.g., tensorflow, keras, pytorch, CAFFE).
• Excellent interpersonal and communication skills, as well as writing skills.
• Strong team and engineering leadership with system integration skills and ability to work on research translational activities into commercial deployment
• Proficiency in English language.
Prioritized Requirements:
• Work experience in/related to machine learning, and in particular (distributed) reinforcement learning.
• Experience with traffic related problems, and transportation theory.
• Experience with robot/traffic simulation, and translation of simulations into robotic prototypes.
• Good publication records in international leading journals.
