The Data Science of the Natural Environment (DSNE) project is a 4-year, £2.6M interdisciplinary research programme that brings together environmental scientists, computer scientists, data
scientists and statisticians from Lancaster University and the Centre for Ecology and Hydrology.
Associated with DSNE, we are advertising several PhD positions across environmental data science, including those that are environment-led, methods-led and social science-led. It is expected that we will fund 5 PhD positions from
the range of projects that we are advertising.
Detailed information on the advertised PhD projects can be found here, including information on the application process. Titles of the projects are
listed at the end of this message.
Application deadline: 5pm (GMT), 11th February 2019 (extended by popular demand!)
General enquiries: firstname.lastname@example.org
Unfortunately, the PhD funding is only for UK and EU applicants.
Available PhD project titles
Data science approaches to projecting future global-to-local air quality and climate
Robust assessment of change points in air quality looking across scales and across multiple data sources
Decision making in the face of uncertainty: A qualitative study
Understanding trust in environmental data science: Cross disciplines and cross cultures
Non-parametric mixture methods for improved satellite altimeter retrievals over ice sheets
Diagnosing Antarctic ice shelf risk using coupled computational modelling
Automated quantification of Greenland ice sheet melting using spaceborne radar data and multivariate changepoint methods
Downscaling and cross-scale integration of land use data and models for building pathways towards sustainable food and land use systems
Integrating agent-based land use models and macro models for improved environmental decision-making
Mapping the rates of changes in land physical properties using remote sensing data
Statistical modelling and physical drivers of extreme hydrological events