PhD opportunity: (Tele)commuting, cities and weather conditions

ESRC funded PhD Studentship for DREAM CDT October 2016 Intake

This project aims to explore the relationship between (tele)commuting and weather. Researchers have spent significant effort in modelling the effects of weather conditions and also extreme weather events on commuting and transport infrastructure. Also, prior research has tried to understand the role that Information and Communication Technologies (ICTs) can perform as an enabling platform for working remotely and avoiding or decreasing physical commuting. This PhD project will build upon these two streams of research and also incorporate a risk dimension which is related to extreme weather and climate change. For instance, changes to the daily commute can be made during extreme weather (e.g. floods, heatwaves, snow), allowing commuters to select the mode of transport which is most resilient for the conditions. At the extreme, telecommuting can be seen as a powerful tool to increase resilience.

Cities are organised in space as complex urban networks, which are connected together through various diverse layers of infrastructure (from transport to digital infrastructure). These infrastructural layers vary from city to city and will affect the capacity of individuals to commute. With respect to telecommuting, the complexity of the above argumentation increases if we consider labour and housing markets. For instance, not every industry can support and take advantage of telecommuting opportunities. Similarly, people whose occupation enables telecommuting may reside in close proximity or in areas of similar socio-economic profile. For instance, problems with Internet broadband connectivity in rural areas might still be a deteriorating factor for working from home and avoiding physical commuting. This PhD project will build upon the above narrative and answer research questions related with the capacity of places and individuals to telecommute, the relation of telecommuting with with weather and extreme weather events, and the link between infrastructure – both digital and transport infrastructure – with telecommuting.

A key partnership with Enable ID has already been secured, which will provide a wealth of stream data in regards to personal mobility. This PhD project will introduce a framework of diverse analytical methods which include statistical analysis such as multi-level modelling, data mining, network analysis, spatial analysis and visualisation.NWM-CONCESSIONARY-NOV01-1020PX.JPG

Supervisors: Dr Emmanouil Tranos and Dr Lee Chapman

About DREAM CDT

With four leading universities: Cranfield, Birmingham, Cambridge and Newcastle – and over twenty informatics industry organisations collaborating to deliver leading edge research and training through the DREAM Centre for Doctoral Training, all you have to decide is where you want to make a difference.

The DREAM CDT programme offers an attractive stipend with a strong professional development ethos. The programme provides a research experience combining academic rigour with real world problem solving, ensuring you have the opportunities to progress your career in the global informatics sector. Researchers will study for a PhD, benefiting from expertise, events and courses run at all four of the partner universities.

Application

If you are interested in joining us in DREAM to study for a PhD in Big Data, Risk and Environmental Analytical methods, the 2016 call for projects has now been opened for applications, closing on Friday, 26th February, 2016 at midnight. The application form is available here and needs to be sent by email to Dr Emmanouil Tranos.

Eligibility

*To be eligible for this funding, applicants must be a UK / EU national. We require that applicants are under no restrictions regarding how long they can stay in the UK i.e. have no visa restrictions or applicant has “settled status” and has been “ordinarily resident” in the UK for 3 years prior to start of studies and has not been residing in the UK wholly or mainly for the purpose of full-time education.

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