Geographic Data Science
- PhD
Overview
This program trains the next generation of geographic data and quantitative social scientists who are interested in understanding how to use data science and other quantitative methods to tackle pressing geospatial challenges in social and natural environments. Examples of geographic data-driven methods include but are not limited to statistical methods; machine learning; artificial intelligence; GIS; earth observation and social sensing; cartography and data visualization; data infrastructure and management; and causal inference. Geospatial challenges can be broadly interpreted as any problems that involve using geospatial data. Particularly, potential supervisors at the University of Bristol have expertise in policy, demography, social inequality, social geography, sustainability, human mobility, digital economy, cities, health, climate science, education, and so on.
In contrast to its sister programs, PhD in Human Geography and PhD in Physical Geography, this program emphasises methodological innovation and application. It is aimed at those interested in advancing existing computational methods or applying state-of-the-art digital and data-driven techniques to any topics that are related to geography. We welcome applicants from any relevant background, such as geography, social science and policy, statistics, computer science, cognitive science, and environmental science.
Entry requirements
An upper second-class degree (or equivalent qualification) with substantive (geographic) data science (at least 60 credits plus a (geographic) data science-focused dissertation).
See international equivalent qualifications on the International Office website.
Read the programme admissions statement for important information on entry requirements, the application process and supporting documents required.
Go to admissions statementIf English is not your first language, you will need to reach the requirements outlined in our profile level B.
Further information about English language requirements and profile levels.
Fees and funding
- Home: full-time
- £4,850 per year
- Home: part-time (two years)
- £2,425 per year
- Overseas: full-time
- £26,700 per year
Fees are subject to an annual review. For programmes that last longer than one year, please budget for up to an 8% increase in fees each year.
More about tuition fees, living costs and financial support.
Alumni discount
University of Bristol students and graduates can benefit from a 25% reduction in tuition fees for postgraduate study. Check your eligibility for an alumni discount.
Funding and scholarships
ESRC South West Doctoral Training Partnership (SWDTP);
University of Bristol Scholarships;
Or contact potential supervisor(s) for other opportunities.
Further information on funding for prospective UK and international postgraduate students.
Career prospects
Our students go on to employment in a wide variety of areas - often where statistical analysis and data science skills are required. Students also continue within academic careers, going on to post-doctoral and lecturing positions.
At its core, the programme establishes a sound research training base, together with a set of bespoke training courses that provide students with the advanced (geographic) data science toolkit and research methods required for their PhD topic. It also provides a foundation for diverse types of employment, including research, policy and intervention implementation.
Meet our supervisors
The following list shows potential supervisors for this programme. Visit their profiles for details of their research and expertise.
Contact us
- Contact
Izzy Montgomery, Postgraduate Student Administrator
- Phone
- +44 (0)
117 928 7878
geog-pgadmis@bristol.ac.uk
- Contact
Dr Rui Zhu, Programme Director
rui.zhu@bristol.ac.uk