Job Postings

Four fully funded BigData PhD studentships at the University of Leeds


More information below, or for full details, and how to apply, see the website. The deadline is 31st March.

http://www.lida.leeds.ac.uk/phd.html

The University of Leeds is seeking talented and highly motivated doctoral researchers to join the Consumer Data Research Centre (CDRC) which is being established with funding from the Economic and Social Research Council’s (ESRC) Big Data Network. Deadline for applications: 31st March

New data relating to both the social and physical world are being created at an increasing rate, and with great variety. These sources, often characterised as “Big Data”, have been identified by the UK Government and Research Councils as one of eight great technologies that will power scientific developments and economic growth over the next decade. This commitment has been matched by more than £360 million of government funds for big data research and infrastructure at UK universities. Independent reports suggest that big data analytics could add £216 billion and 58,000 new jobs to the UK economy over the next three years.

The CDRC will be part of the Leeds Institute for Data Analytics (LIDA), which is now being established with more than £20 million of funding from the University and four major research councils (including the ESRC). The city of Leeds is already recognised as a hub for big data in business, health care and academic research. LIDA will move the University even further to the forefront by combining projects in consumer data research, medical bioinformatics, digital humanities and monitoring environmental change to provide a truly multi-disciplinary approach to this exciting and challenging field.

As part of this initiative we are offering four ESRC funded studentships to work on consumer data, which are generated by retailers, utilities and various service organisations in both the commercial and non-commercial sectors. Studentships will be available for both three years and four years depending on prior experience and training, and will focus on four topics:

Project A: Urban Mobility and Movement Patterns

Supervised by Professor Mark Birkin and Dr Nick Malleson in the School of Geography this project will use consumer data sources to focus on the critical interrelationships between time and space, and how this impacts on the local movements of people. Through a combination of big data analysis and advanced geographical modelling it will, for the first time, create a highly detailed picture of patterns of consumer behaviour that will be extremely relevant for businesses, academia and wider society.

Project B: Ethical Consumption

Supervised by Professors Matthew Robson and Wandi Bruin de Bruine in Leeds University Business School this project will develop and test a model of consumer purchasing motivations and behaviour that suggests ethical sensitivity is subject to a complex set of drivers. The backbone of the project will address Ethical shopping behaviour by combining financial data, weather data, and mobile phone data to explain variations in consumption motivations reflected in their ethical shopping behaviours.

Project C: Big data and the development of omni-channel business geography

Supervised by a team comprising Professors Susan Grant Muller, Graham Clarke and Martin Clarke from the Faculty of Environment this project will explore the usefulness of different kinds of consumer data for retailers and local authorities in the planning and delivery of local services (in particular transport and land use planning).

Project D: Changing the behaviours, habits and practice around the use of household surface cleaning products

Supervised by Professors William Young (Sustainability Research Institute), Chris Rayner (Chemistry) and Wandi Bruin de Bruine (Business School), this project will work in collaboration with ASDA (a major UK supermarket chain) to understand and influence patterns of use of household surface cleaning products to reduce associated environmental and health problems

Discussion

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept