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 visit our website
http://jobs.earlham.ac.uk/ or contact the Human Resources team on 01603 450814 or
[email protected] 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.
