Student led projects
Click here for instructions on how to apply
*This opportunity is only open to Home rated applicants (UK citizens or those with indefinite leave to remain in the UK)*
The Centre for Doctoral Training in Data Analytics and Society is inviting applications for student-led projects to start in October 2023. We have up to 4 funded places to offer to students who wish to put forward their own proposals for a PhD project in the area of Data Analytics and Society.
We would be particularly interested in projects that explore the area of new methodologies for working with new forms of Data and at projects that look at the ethics of working with this data.
You will be registered on the Data Analytics and Society +4 PhD integrated MSc and PhD programme, details can be found on our website here – https://datacdt.org/overview/
The research proposal must fit the remit of the ESRC and also our Centre:
Our Centre funds project that:
- Promote the creation and analysis of new longitudinal and streamed data resources for socio-economic investigations.
- Create new methods (e.g. scaling up existing methods for real time big data analytics; explore new approaches for estimating intersectional inequalities),
- Investigate social processes (e.g. virtualisation of retailing; data-driven decision making and social behaviours; quantify the dynamics of ethnic and socio-economic segregation)
- Facilitate interventions (e.g. create decision support tools for policy makers; resource targeting, network planning, social media apps for diet, travel, lifestyle planning).
Your project must be social science-led and at least 50% within ESRC’s remit, we would encourage you to work with supervisors in multiple disciplines where that is appropriate.
You will need to identify data which could be used in your project, this could be open data such as that available through Government https://data.gov.uk/ or you may want to look at ESRC data resources for example Data from the Consumer Data Research Centre https://data.cdrc.ac.uk/. You may also want to work with data you know or have access to through an employer or other contact in an organisation so that you have an external partner as our partner-led project students have.
Please be aware that some data may require a separate application process in order to gain access and you should be clear in your application about the data you plan to use and any restrictions to access that may be in place.
To submit a proposal
In order to apply, please first contact a potential PhD supervisor from one of our host universities which are Leeds, Liverpool, Manchester and Sheffield (please see links at the bottom of this page). You can then follow the application instructions on our webpage, but include your research proposal in the appropriate section. https://datacdt.org/entry-criteria-applying/
You will need the supervisor to provide a letter of support for your project, please share the supervisor statement form with them early in the process and include it with your application.
Please note – you must apply through the Leeds portal, even if you wish to study at one of our partner institutions: https://studentservices.leeds.ac.uk/pls/banprod/bwskalog_uol.P_DispLoginNon
Do not apply directly to Liverpool, Manchester or Sheffield.
following *Please note, this opportunity is only open to Home rated applicants*
Finding a Supervisor
You can find potential supervisors by looking at who our current supervisors or looking at the appropriate departments in the universities.
Our current projects with supervisor details can be found here https://datacdt.org/meet-the-students-2/
Information about our institutions and the people who are linked to them can be found here https://datacdt.org/the-partners/
University of Leeds supervisor search: https://phd.leeds.ac.uk/
University of Liverpool Geographic Data Science Lab: https://www.liverpool.ac.uk/geographic-data-science/our-people/
University of Manchester Cathie Marsh institute: https://www.cmi.manchester.ac.uk/about/people/
University of Sheffield Methods institute: https://www.sheffield.ac.uk/smi/people/academic
If you need support finding an appropriate supervisor, please email DataCDT@leeds.ac.uk with information about your project and we will endeavour to direct you to an appropriate academic.