PhD Student for Projects within the Singapore-MIT Alliance for Research & Technology, Future Urban Mobility, Singapore

Studentship program for doctoral Studies to be supervised by NTU and MIT faculty.

Study Subject:Engineering
Employer: NTU & MIT
Level: PhD
Scholarship Description: The Future Urban Mobility (FM) Interdisciplinary Research Group is the fourth and most recent IRG established within the Singapore-MIT Alliance for Research and Technology (SMART). The FM IRG’s activities began officially on July 1, 2010.
The goal of the FM IRG is to develop, in and beyond Singapore, new paradigms for the planning, design and operation of future urban mobility systems. Innovative urban mobility systems, aimed at both passengers and freight, will materially enhance sustainability and societal well-being on a global scale. This is a particularly opportune time to address this topic due to a confluence of relevant developments: major advances in computing, communications, and sensing technologies; the great progress that has been made in recent years in our ability to model, evaluate and optimize urban mobility systems; the growing importance of environmental sustainability issues; the aging of physical infrastructure in developed countries and the need for massive new infrastructure in less developed ones; and the vast economic stimulus that can be provided by the modernization and renewal of urban mobility systems worldwide.

The FM IRG will:
- harness and enhance promising networked computing and control (NCC) technology-enabled innovations that may contribute to improved future urban mobility;
- develop decision models that can be applied to support various novel mobility concepts, such as the pervasive use of real-time information, mobility-on-demand services and green logistics;
- investigate the potential and impacts of these innovations and decision models; and
- assess their implications for urban development and urban planning organizations and institutions.

The concrete project is the following:
Real-time Path Tracking/Predictions and On-Demand Route Guidance Under Uncertainty
Develop algorithms that use real-time data to (i) track and predict paths in dynamic transportation networks, and (ii) provide on-demand route guidance under uncertainty.
Please send detailed curriculum vitae, statement of research interests, three references, and relevant publications (if applicable) electronically to:
Prof. Justin Dauwels
Nanyang Technological University
School of Electrical & Electronic Engineering

Scholarship Application Deadline: Contact Employer

Further Scholarship Information and Application

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