Program Overview

Advanced Quantitative Methods

Overview

The Advanced Quantitative Methods (AQM) pathway is designed to foster research that pushes the boundaries of quantitative methodologies in the social sciences. AQM is fundamentally about methodological innovation and application. It aims to support research that either advances existing quantitative methods or applies cutting-edge techniques to social science topics.

The pathway aims to promote research that employs sophisticated statistical, mathematical, econometric, and computational modelling techniques. This includes, but is not limited to, process modelling, machine learning, and artificial intelligence. Projects may involve applying statistical methods used in other disciplines to social science problems, or developing novel statistical methods for analysing social-science data.

Key Information

• Programme duration: PhD - up to four years full-time; up to eight years part-time.
• Start date: September 2025
• Delivery method: On-Campus
• Location: Clifton
• Awards available: PhD

World-leading Research

• The University of Bristol is ranked fifth for research in the UK (Times Higher Education).
• 94% of our research assessed as world-leading or internationally excellent.

Entry Requirements

• At least a 2:1 in a relevant subject, or a master's qualification, or be working towards a master's qualification, or international equivalent in a relevant field.
• English language requirements: If English is not your first language, you will need to reach the requirements outlined in our profile level D.

Fees and Funding

• UK: full-time - £4,850 per year
• UK: part-time (two years) - £2,425 per year
• Overseas: full-time - £21,300 per year
• Alumni discount: University of Bristol students and graduates can benefit from a 25% reduction in tuition fees for postgraduate study.
• Funding and scholarships: This pathway is part of the Economic and Social Research Council (ESRC) South West Doctoral Training Partnership for the South West (SWDTP), offering opportunities for funded PhD studentships.

Career Prospects

This programme provides outstanding academic and research training for prospective PhD students and can lead to careers in data and quantitative research.

Meet Our Supervisors

• Professor William Browne
• Professor Richard Harris
• Professor George Leckie
• Professor Kate Tilling
• Dr Richard Timmerman
• Professor Emmanouil Tranos
• Dr Winnie Wang
• Dr Levi Wolf
• Dr Rui Zhu

Research Groups

• Quantitative Spatial Science (QuSS) Research Group – School of Geographical Sciences

How to Apply

• Apply via our online application system.
• Application deadline: Please contact the course administrator for details on application deadlines.
• Preliminary contact with staff from the department is welcome at any time of the year. We strongly encourage prospective applicants to contact us early, before submitting an application.