About the Project
Primary Supervisor - Professor Ke Li
Plants survive drought, heat and disease by rapidly changing which genes are switched on, where, and when. But we still cannot reliably design the regulatory DNA that controls these expression patterns. This PhD asks an ambitious question: can explainable AI discover plant DNA “design rules” that are strong enough to survive experimental testing?
You will join Earlham Institute’s AI for Biology group led by Professor Ke Li. As one of the most active AI groups in the UK, you will work in a highly supportive and collaborative group, equipped with unique technical platforms for building in-house large-scale foundation models. You will receive scientific training in foundational AI methods and push the boundary of AI for biology. Meanwhile, you will also develop skills in experimental design, reproducible software and FAIR data management.
You will also obtain complementary experience in plant genomics and engineering biology, supported by Prof. Anthony Hall’s plant genomics expertise and Dr Carolina Grandellis’s Earlham Biofoundry team. You will collaborate with experimentalists on the design of compact libraries of cis-regulatory modules, assemble them into a standard reporter system and test them in potato protoplast assays. Successful and failed designs will both be valuable: they will reveal which AI-derived rules are biologically meaningful, where models fail, and how future design cycles should be improved.
The project will be conducted at the Earlham Institute, a world-class BBSRC research centre of excellence in genomics, engineering and computational biology, and AI. You will join a highly collaborative and supportive research community, interact with AI researchers, plant scientists, bioinformaticians, automation specialists, and have access to training and career development opportunities across the Norwich Research Park through the Norwich Research Park Biosciences Doctoral Training Partnership.
The Norwich Research Park Biosciences Doctoral Training Programme (NRPDTP) is offering fully funded studentships for October 2027 entry. The programme offers postgraduates the opportunity to undertake a 4-year PhD research project whilst enhancing professional development and research skills through a comprehensive training programme. You will join a vibrant community of world-leading researchers. All NRPDTP students undertake a three-month professional internship placement (PIPS) during their study. The placement offers exciting and invaluable work experience designed to enhance professional development. Full support and advice will be provided by our Professional Internship team.
This project has been shortlisted for funding by the NRPDTP. Shortlisted applicants will be interviewed on the 2nd, 3rd and 4th February 2027.
Visit our website for further information on eligibility and how to apply: https://biodtp.norwichresearchpark.ac.uk
Our partners value diverse and inclusive work environments that are positive and supportive. Students are selected for admission without regard to gender, marital or civil partnership status, disability, race, nationality, ethnic origin, religion or belief, sexual orientation, age or social background.
To maximise accessibility and attract students from underrepresented groups to our programme we have introduced bespoke templates for applicant Personal and Research statements which will enable every applicant to fully represent themselves through providing suitable examples and evidence. These forms are on the NRPDTP website and must be used for these sections of the application form.
Entry requirements
At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5 overall, 6 in each category).
Mode of study
Full-time
Start date
1 October 2027
Funding Notes
This project is awarded with a 4-year Norwich Research Park Biosciences Doctoral Training Partnership PhD DTP studentship. The studentship includes payment of tuition fees (directly to the University), a stipend to cover living expenses (2026/27 stipend rate: £21,805, and a Research Training Support Grant of £5,000pa for each year of the studentship.
References
H. Yu, et al. An interpretable RNA foundation model for exploring functional RNA motifs in plants, Nature Machine Intelligence, 6: 1616-1625, 2024.
H. Yang, et al. Bridging Sequence-Structure Alignment in RNA Foundation Models, AAAI 2025, 39(20): 21929-21937.
H. Yu, et al. PlantScience.ai: An LLM-powered virtual scientist for plant science, Molecular Plant, 19(5): 1117-1123, 2026.
S. Zhou, et al. Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods, ICML 2026.
M. Huang, et al. Conversational exploration of literature landscape with LitChat, IJCAI 2025, p. 11058-11061.