-
person. Aims: The project aims to develop and evaluate AI methods for medical image analysis to detect diabetic retinopathy, glaucoma, cataract and age-related macular degeneration (AMD). As
-
statistical and data analysis frameworks are welcomed to be proposed or developed by the candidate as part of the project. We will apply the methodologies to a wide range of data from observations to modelling
-
advanced nanoengineering techniques, the project seeks to achieve a DA biosensor with superior sensitivity, selectivity, and stability, optimised for use in complex biological environments. Background
-
role in shaping the research direction by selecting study regions, refining analytical approaches, and integrating methods across atmospheric science, remote sensing, and epidemiology
-
. The key objectives are: Objective 1: Identify optimal FPV sites in Cornwall and the South-West using GIS and multicriteria analysis to maximise green hydrogen potential, while evaluating legal frameworks
-
geospatial analysis in R, alongside advanced modelling with JULES. Co-supervisors in Brazil will provide field and logistical expertise, while the Met Office will offer world-class training in modelling and
-
expand current technology to include automated live analysis, integrating machine learning algorithms capable of interpreting the complex behavioural patterns of mussels in response to environmental stress
-
dynamics and, if appropriate, field work (Nicholas, Aalto); numerical modelling (Nicholas, Hawker); machine learning (Hawker, Aalto); and analysis of remote sensing (Aalto) and population datasets (Hawker
-
communities may have ecosystem level impacts that must be considered as part of sustainable management of the deep ocean, and in light of the new High Seas Treaty. This studentship will ask: how are deep-water
-
than on preserving individual species. This approach could create well-functioning ecosystems, resilient to threats such as climate change. But how do we measure and conserve ecological processes in