Senior Computational Biologist - AI & Rare Disease Digital Twins

Earlham Institute; Norwich; On-site; GBP 47,000 - 58,000; Full time

Job summary

The Earlham Institute in Norwich, UK invites applications for a Senior Computational Biologist to join the AI-integrated Digital Twins Group. You will analyse and integrate multi-omics data, map patient data onto Digital Twin models, and lead their biological application and validation, developing hybrid modelling approaches that combine omics representations with AI/ML predictions.

This is a full-time, fixed-term two-year post with potential extension; salary £47,450–£58,000 per annum,

Qualifications

• Strong expertise in bioinformatics/omics.
• Excellent Python and/or R skills.
• Experience with machine learning/statistical modelling.

Responsibilities

• Analyse and integrate transcriptomic, single-cell and other multi-omics/phenotypic data.
• Map patient data onto reusable Digital Twin models.
• Construct and personalise hybrid Digital Twins.
• Lead their biological application and validation.

Skills

Bioinformatics/omics

Python

R

Machine learning

Single-cell data

Multi-omics integration

Network biology

Deep learning

Hybrid modelling

Job description

Applications are invited for a Senior Computational Biologist 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 integrates patient multi-omics data with mechanistic models, GenAI and other machine-learning approaches. It is co-led by Dr Rahuman Sheriff, Ellen McDonagh (Open Targets/EMBL-EBI) and Evangelia Petsalaki (EMBL-EBI). The postholder will closely collaborate across their teams.

The role:

You will provide the biological and computational bridge between rare-disease data, AI/ML and executable mechanistic models. You will analyse and integrate transcriptomic, single-cell and other multi-omics/phenotypic data, map patient data onto reusable Digital Twin models, construct and personalise hybrid Digital Twins, and lead their biological application and validation.

This is not a conventional bioinformatics-only role. You will work with the Mechanistic Modeller and AI/ML Scientist to develop hybrid modelling approaches that combine omics-derived representations, AI/ML predictions and executable models, and apply these systems to in-silico perturbation and disease-mechanism questions.

The ideal candidate:

You will have strong expertise in bioinformatics/omics, excellent Python and/or R skills and practical experience with machine learning/statistical modelling. Experience with single-cell data, multi-omics integration, network biology, deep learning, mechanistic modelling or hybrid modelling would be advantageous.

The post holder must be able to evidence scientific independence, leadership of substantial computational work and the ability to coordinate interdisciplinary research with limited supervision.

Additional information:

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

Salary on appointment will be within the range £47,450 to £58,000 per annum depending on qualifications and experience.

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.