Aotearoa New Zealand has internationally significant linked data infrastructure and longitudinal studies, but the potential for addressing major health and environmental challenges remains underused.
Many studies still rely on cross-sectional data or measure “place” only as the neighbourhood where someone lives at one point in time. This limits our ability to understand how changing environments, services, infrastructure, and social conditions shape health across an individual’s lifecourse from birth onwards. This PhD will develop new computational and geospatial infrastructure to strengthen how linked data can be used for real-world benefit.
The student will build transferable approaches for connecting longitudinal health and social data with environmental information such as drinking water infrastructure, nitrate exposure, community water fluoridation, air pollution, greenspace, deprivation, and access to services. Applied examples may include HRC-funded work on nitrate exposure and health led by Chambers, and HRC-funded work on community water fluoridation and oral health led by Hobbs.
The project would suit a student interested in linked data, geospatial science, public health, environmental health, data science, or policy-relevant research. Its wider contribution is a reusable methodological framework that can support better evidence for healthier communities, stronger environmental decision-making, and more resilient futures in New Zealand and internationally.
Supervisors
Primary Supervisor: Associate Professor Matthew Hobbs
Other Supervisor(s): Professor Elena Moltchanova
Key qualifications and skills
We are looking for a quantitatively strong student with interests in linked data, geospatial science, public health, environmental health or spatial data science.
Applicants should have experience working with complex data and ideally be proficient in R, Python or a comparable analytical language. Experience with GIS, longitudinal or administrative data, epidemiological methods, or spatial-temporal analysis would be advantageous but is not essential.
The successful candidate should have strong analytical, problem-solving and communication skills and an interest in developing reproducible computational methods for real-world health and environmental research.
Does the project come with funding
Per annum: Stipend of $32,650 plus PhD tuition fees. The project also has up to $5,000 available for research expenses across the duration of the degree.
Funding duration: Three years (360 points)
Final date for receiving applications
27 October 2026
How to apply
This is a UC Commitments Doctoral Scholarship and applications must be made through the Scholarship Portal in your myUC account. Emailed applications will not be considered. Find out more here: University of Canterbury Scholarship Portal - UC Commitments - Computational infrastructure for linked data, health and environmental resilience
Keywords
public health; data science; spatial; environment; geospatial
