SWDTP Advanced Quantitative Methods studentship

Applications close on 14 January 2025 (12:00 noon UK time) and the studentship will start on 1 October 2025

Apply

To apply for the SWDTP Advanced Quantitative Methods pathway please use the online application form. Simply click on the ‘online application’ link below for PhD Mathematics and Statistics :
Within the Research section of the application form, in the following fields, please add:
  • Proposed project title/studentship title: add your project title
  • Proposed supervisor: add the potential supervisor’s name
  • Studentship code: add SWDTP 25-10 AQM

Application guidance

It is important that you follow the instructions above or your application for this studentship may be missed and therefore will not be considered.
Before applying, please ensure you have read the Doctoral College’s general information on applying for a research degree .
For more information on the admissions process, please contact research.degree.admissions@plymouth.ac.uk.
Centre for Mathematical Sciences (Faculty of Science and Engineering) and Â鶹´«Ã½ Institute of Health and Care Research (Faculty of Health)
The Advance Quantitative Methods (AQM) pathway is for social science researchers who wish to learn and develop advanced quantitative methods and apply them to answer substantive questions from their discipline. It is also well-suited for statistically trained researchers whose interests are more methodological. You will be part of an interdisciplinary research group interested in the development and application of advanced quantitative methods to address research questions in social sciences. Projects may involve applying statistical methods to address social science problems, or developing novel statistical methods for analysing social-science data.
The AQM pathway at the Â鶹´«Ã½ is part of the Economic and Social Research Council (ESRC) , offering opportunities for funded PhD studentships.
Research in AQM at Â鶹´«Ã½ is carried out in various research centres, including the Â鶹´«Ã½ Institute of Health and Care Research (PIHR) , the Centre for Mathematical Sciences (CMS) and the Big Data group . Joining this pathway, you will benefit from insights from a number of disciplines and research groups, including data science, health, psychology, mathematics and statistics.
Successful applicants will be part of a large, vibrant, highly collaborative community of PhD students with good interdisciplinary links, providing opportunities for research, training, and collaboration.