-
(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
-
; elsewhere, exposure sustains disinvestment. This PhD investigates these dynamics, known as hazard gentrification, and asks how cities can design adaptation that is resilient and socially just. You will build
-
This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
-
-26-LU4 in your application. This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen at https
-
relevant subject. English language requirements: Applicants must meet the minimum English language requirements. Further details are available on the International website (http://www.lboro.ac.uk
-
, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
-
by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large