Published: 29 Dec 2025 310 views
Leveraging AI, 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 databases. Integrating image- and text-derived datasets poses challenges due to differences in scale, structure, and accuracy, requiring robust data fusion and validation.
By combining these AI-derived trait datasets with phylogenies and environmental variables, the project aims to rapidly explore trait evolution, predict dispersal potential, and assess climate-related risks. This work bridges biodiversity science and cutting-edge AI, offering an innovative framework for trait-based research.
The entry requirements are listed using standard UK undergraduate degree classifications i.e. first-class honours, upper second-class honours and lower second-class honours.
Entry requirements for United Kingdom
Applicants will normally need to hold, or expect to gain, at least a 2:1 degree (or equivalent) in Geography, Biology, Chemistry, Earth Science or Environmental Science, Computer Science, Engineering, or an appropriate Master’s degree.
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website.
For more details, visit Loughborough University Scholarship webpage
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