"PhD Studentship: AI-Driven Trait Analysis of Fruit Evolution and Climate Vulnerability"

Fleshy-fruited Myrtaceae, comprising nearly half of the ~6,000 species, represent a key evolutionary innovation linked to diversification and dispersal. This project investigates the ecological and evolutionary roles of fleshy fruits in two hyperdiverse tribes, Myrteae and Syzygieae, examining how fruit and seed traits influence niche dynamics, dispersal, and climate vulnerability. 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.

Entry requirements:

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.

Funding information:

This studentship which is partially funded by NERC, provides a tax-free stipend of £20780 per annum (in 2025/26) and tuition fees at the UK rate for 3.5 years. It also provides a Research Training Support Grant (RTSG) of £8,000. Due to UKRI funding rules, no more than 30% of the studentships funded by this grant can be awarded to International candidates, but successful International candidates will have the difference between the UK and International tuition fees provided by the University.

How to apply:

1. Complete a CENTA studentship application form in Word format (available from https://centa.ac.uk/apply/) under the ‘Our project-based studentships’ section on that page
2. All applications should be made online via the above ‘Apply’ button. Under Campus, please select ‘Loughborough’ and select the Programme “School of Science/Computer Science”. Please quote the advertised reference number CENTA2026-LU01 in your online application.
3. During the online application process please upload the CENTA studentship application form and a CV in addition to the other required minimum supporting documents.
4. Application closing date is midnight (UK time) on Wednesday January 7th 2026. Interviews for short-listed candidates are expected to be held sometime in the period Monday February 2nd – Friday February 13th 2026.