Postdoctoral Research Scientist - Generative AI & Digital Twins

Applications are invited for an AI/ML Postdoctoral Research Scientist to join Dr Rahuman Sheriff's AI-integrated Digital Twins Group at the Earlham Institute, based in Norwich, UK.

Background:

The post is part of a Chan Zuckerberg Initiative-funded collaboration between Earlham Institute, Open Targets and EMBL-European Bioinformatics Institute, developing open-source hybrid Digital Twins for rare diseases The programme uses large-scale biological data and mechanistic simulations to address the scarcity and sparsity of rare-disease patient data, and integrates GenAI, other ML approaches and executable mechanistic models. It is co-led by Dr Rahuman Sheriff, Ellen McDonagh (Open Targets/EMBL-EBI) and Evangelia Petsalaki (EMBL-EBI).

The role:

You will continue and advance the programme's GenAI/ML methodology, developing models for biological representation learning, multi-omics imputation and perturbation-response prediction. Potential approaches include generative models, transformers, VAEs, multimodal architectures, transfer learning and biological foundation models where scientifically appropriate.

A major focus will be hybrid mechanistic-AI modelling. You will work with the Mechanistic Modeller and Computational Biologist to connect learned representations and predictions with executable models, use mechanistic simulations for training or validation, and develop uncertainty-aware, robust and biologically meaningful prediction systems for rare-disease Digital Twins.

The CZI programme is co-led by Dr Rahuman, Ellen McDonagh (Open Targets/EMBL-EBI), whose expertise includes rare-disease genetics, pharmacogenomics, target prioritisation and data integration, and Evangelia Petsalaki (EMBL-EBI), whose research includes context-specific cell signalling, causal and phenotype-specific network inference and machine learning. The post holder will work across this interdisciplinary collaboration and with the wider rare-disease and modelling communities

We may consider appointing candidates that can operate at a higher level and salary, providing they meet the outlined criteria for the senior position.

The ideal candidate:

You will have excellent Python and modern deep-learning skills and practical experience developing AI/ML methods. We welcome candidates from AI/ML, computer science and quantitative disciplines as well as computational biology. Biological-data experience is advantageous but strong AI/ML candidates motivated to work on biological problems are encouraged to apply.

For appointment at a higher grade, the postholder must be able to take greater intellectual and operational leadership of a defined AI/ML methodology workstream. We expect evidence of methodological independence, leadership of substantial research outputs and the ability to lead a defined AI/ML workstream with limited supervision.

Additional information:

This is a full-time post for a contract of 2 years, with the possibility for extension depending on funding.

Salary on appointment will be within the range £39,000 to £46,500 per annum depending on qualifications and experience. A starting salary of £40,100 is guaranteed for candidates who can evidence their PhD certificate at appointment; those awaiting confirmation of their PhD award will be appointed at £39,000 until evidence is provided.

For further information and details of how to apply, please click the 'Apply' button above or contact the Human Resources team on 01603 450814 or nbi.recruitment@nbi.ac.uk quoting reference 1006215.

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 6 December 2026.

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