Earlham Institute
Postdoctoral Research Scientist
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(Senior) Postdoctoral Research Scientist – Generative AI and Closed-loop Discovery
Applications are invited for a Postdoctoral Research Scientist or Senior Postdoctoral Research Scientist to join Professor Ke Li's AI for Biology Group in the Research Faculty of the Earlham Institute, based in Norwich, UK.
Background
The AI for Biology Group will be newly established at the Earlham Institute (EI), while building on Professor Ke Li’s established and well-funded research programme in fundamental AI, AI co-scientists, and applications in complex scientific domains such as RNA sequence-function modelling, structure prediction, and inverse design.
At EI, the group will develop an ambitious Generative Digital Biology (GDB) programme, developing multimodal, cross-organism and experimentally grounded AI systems that can learn from biological data, support hypothesis generation, guide experimental design, and accelerate discovery across EI's research programmes and technology platforms.
The successful candidate will have access to substantial AI compute, including in-house state-of-the-art H200 GPU servers, alongside further capacity through the Norwich Data Centre and access to national-scale AI compute through Isambard-AI. This provides a strong environment for frontier AI development and evaluation. Collaboration with the Earlham Biofoundry provides routes for model-guided experimental design and, where appropriate, closed-loop self-driving laboratory workflows supported by established lab automation.
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The role
We are seeking an ambitious researcher to develop generative AI methods for biological design and closed-loop discovery within a new AI for Biology Group at EI. The successful candidate will create novel AI algorithms that generate and refine biological designs, prioritise experiments, and learn from experimental feedback.
Building on Professor Ke Li’s established research programme, the role focuses on developing new AI methods for scientific discovery rather than simply applying existing approaches. The post offers extensive collaboration across the Institute, supporting AI-guided design-build-test-learn workflows, biological discovery, and the development of open algorithms, benchmarks, and reproducible research.
Ideal candidate
The successful candidate will have a PhD (awarded or expected within 6 months) in Computer Science, AI, Machine Learning, Computational Biology, Mathematics, Statistics, Physics, Engineering, or a related quantitative discipline.
They will have excellent Python programming skills and practical experience with leading AI frameworks such as PyTorch, JAX, or TensorFlow, together with strong expertise in modern AI methods and depth in one or more of generative modelling, reinforcement learning, Bayesian optimisation, active learning, uncertainty quantification, causal modelling, or optimisation in complex search spaces.
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Candidates should demonstrate experience developing original AI methods for scientific discovery, design, optimisation, or decision-making rather than solely applying existing tools, together with evidence of high-quality research outputs commensurate with career stage. Experience at the interface of AI and biology, including biological foundation models, sequence design, genomics, single-cell data, synthetic biology, or drug discovery, would be advantageous.
Additional information
- Salary on appointment will be within the range £39,000 to £46,500 per annum depending on qualifications and experience for the SC6 level post, and £47,450 to £52,560 per annum for candidates who meet the SC5 level criteria.
- This is a full-time post for a contract of 36 months, with possible extension.
- This role meets the criteria for a visa application, and we encourage all qualified candidates to apply. Please contact the Human Resources Team if you have any questions regarding your application or visa options.
- As a Disability Confident employer, we guarantee to offer an interview to all disabled applicants who meet the essential criteria for this vacancy.
- The closing date for applications will be 04 September 2026.
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