The PhD candidate is expected to carry out cutting-edge research at the interface of engineering, statistics and economics and publish contributions to the emerging literature of data-centric engineering in transportation. This interdisciplinary subject combines mathematical modelling with advances in transportation big data and artificial intelligence.  The overarching aim of this area of research is to build and/or operate old and new infrastructure in smarter, safer ways, making the best use of data. Its core working areas include (but are not limited to):

• Building resilient and robust transportation infrastructure through predictive modelling of urban rail transport operations, analysing large scale usage of roads across different modes, etc.
• Monitoring transportation systems to understand and anticipate the impact of rare and high-consequence events.

 To learn more about data-centric engineering, watch this video produced by the Lloyds Research Foundation. A good textbook reference to the tools and applications for data-centric transportation engineering is:

• Antoniou, C., Dimitriou, L. and Pereira, F. eds., 2018. Mobility patterns, big data and transport analytics: tools and applications for modelling. Elsevier.

Data-Centric Engineering has become a globally recognised academic discipline due to its establishment as a strategic research theme of the Alan Turing Institute, the UK's Institute for Data Science and Artificial Intelligence.  New research findings may get published in general-interest science journals such as Nature, Nature Scientific Communications and Proceedings of the National Academy of Sciences and high-impact area-specific transportation journals such as Transportation Research Part B: Methodological and Transportation Research Part C: Emerging Technologies.

You may be interested in pursuing a PhD in data-centric transportation engineering if

• you hold a degree in transportation science and engineering specifically;
• you are a mathematician with solid background in statistics, and you are interested in developing transportation-specific applications of your skills;
• you are an engineer with good knowledge of mathematical modelling and you intend to expand your methodological skillset with transportation system modelling tools.

This call is not linked to any specific grants or research projects, but we expect applications with a comprehensive research proposal in one of the following topics of data-centric engineering:

1. Application of data science methods and models to big/high dimensional data (such as smartcard data) to identify opportunities for improvement in the operation, planning and design of transportation systems.
2. Development and application of causal inference methods to identify determinants for intervention and forecast impacts.

The PhD candidate is expected to achieve novel research findings and publish contributions to the literature of transport economics. This interdisciplinary subject combines applied welfare economics with transport studies. Its core aim is to model transport markets with microeconomic tools and derive policy recommendations supporting

• Investments into new transport infrastructure (investment appraisal and cost-benefit analysis),
• Transport pricing as a tool of efficient resource allocation (marginal cost pricing, congestion pricing, etc.),
• Regulation of competitive transport markets and the contractual framework of public service provision.

The foundations of transport economics are covered in the following publications:

• Small and Verhoef (2007), The Economics of Urban Transportation. Routledge.
• De Palma, Lindsey, Quinet, and Vickerman (Eds.). (2011). A Handbook of Transport Economics. Edward Elgar Publishing.

Prominent figures of this research area and several members of our group are active in the International Transport Economics Association. New research findings are frequently published in Economics of Transportation and the Journal of Transport Economics and Policy (co-edited by Professor Dan Graham), beside general-interest journals of economics and transport.

You may be interested in pursuing a PhD in transport economics if

• you hold a degree in spatial and transport economics specifically;
• you are an economist with solid background in microeconomic theory and econometrics, and you are interested in transport-related societal problems;
• you are an engineer with good knowledge of transport systems and you intend to expand your methodological skillset with economic modelling tools.

This call is not linked to any specific grants or research projects, but we expect applications with a comprehensive research proposal in one of the following topics of transport economics:

1. The welfare economics of efficient pricing and capacity provision in public transport and emerging shared transport modes (e.g. carsharing, ride-hailing).
2. The wider economic impacts of transport supply; advances in the empirical identification of of wider effects (including external benefits of agglomeration and market access) and applications in investment appraisal.

 The PhD candidate is expected to carry out cutting-edge research at the interface of engineering, statistical and mathematical modelling, and economics and publish contributions to the literature on transit system performance. This interdisciplinary subject involves the application of statistical modelling, machine learning methods, mathematical simulation and optimisation, and transport engineering principles.  The aim of this research area is to analyse, compare, and provide recommendations to improve and/or optimise transit performance across domains of operations including (but not limited to): service provision and quality, demand management, reliability and resilience, maintenance, economic and environmental sustainability, and safety and security. You will work closely with the applied research arm of the Transport Strategy Centre, who undertake performance measurement and analysis of over 100 metro, light rail, bus, rail, and airport operators around the world. Further information on the applied arm of the TSC can be found here.

With increasing access to large scale automated data sets on passenger trips, vehicle movements, and asset condition, among others, the academic research field of transit performance analysis has been rapidly expanding. New research findings may be published in general-interest science journals such as Proceedings of the National Academy of Sciences and high-impact area-specific transportation journals such as Transportation Research Part B: Methodological and Transportation Research Part C: Emerging Technologies.

You may be interested in pursuing a PhD in transit performance analysis if you possess the following background:

• you hold a degree in transportation science and engineering specifically;
• you are a mathematician or computer scientist with a solid background in statistics, and you are interested in developing transportation-specific applications of your skills;
• you are an engineer with good knowledge of mathematical modelling and you intend to expand your methodological skillset with transportation system modelling tools.

This call is not linked to any specific grants or research projects, but we expect applications with a comprehensive research proposal in one of the following topics of transit system performance:

1. Application of advanced statistical and machine learning methods to quantify and analyse transit system performance.
2. Development and application of mathematical simulation and optimisation models to improve transit system performance.