Launch week offerEnds in00h00m00s
annual Promonthly Pro
Earlham Institute
Just Landed
New Today
Postdoctoral Research Scientist in AI-Integrated Digital Twins and Predictive Systems Biology Earlham Institute in United Kingdom
Degree Level
Postdoc
Field of study
Computer Science
Funding
This is a core-funded, full-time 24-month contract with potential extension depending on funding. Salary is £39,000–£46,500 per annum at SC6 and £47,450–£52,560 per annum at SC5, depending on qualifications and experience. Candidates able to evidence their PhD certificate at appointment are guaranteed a starting salary of £40,100; those awaiting confirmation will start at £39,000 until evidence is provided.
Deadline
Dec 2, 2026
Country
United Kingdom
University
Earlham Institute
Apply for this position
Free with an ApplyKite account: the application link, the deadline in your tracker and a check of your fit.
Keywords
Suggested positions
About this position
The Earlham Institute is recruiting a Postdoctoral Research Scientist or Senior Postdoctoral Research Scientist to join Dr Rahuman Sheriff’s AI-integrated Digital Twins Group in the Research Faculty in Norwich, UK.
The group develops predictive models and biological Digital Twins that combine mechanistic understanding, artificial intelligence and machine learning with high-dimensional biological data. Its programme seeks to move beyond association-based prediction by representing biological processes, simulating perturbations and generating testable, interpretable predictions across living systems.
The successful computational scientist will develop methods for predictive systems biology and biological Digital Twins. The research will integrate mechanistic models, AI/ML and multimodal biological datasets to build and test predictive models of cells, tissues, microbial communities and other biological systems.
The role offers substantial freedom for methodological development, including hybrid mechanistic-AI modelling, model personalisation, uncertainty-aware prediction, perturbation and counterfactual simulation, and reusable open modelling workflows. The postholder will interact broadly with the Earlham Institute’s research programmes and technology platforms, with opportunities to work with genomics, single-cell and spatial data, engineering biology and advanced research computing.
The position provides a cross-disciplinary research environment focused on computational biology, scientific machine learning and predictive modelling within the Earlham Institute and its wider Norwich research setting.
Funding details
This is a core-funded, full-time 24-month contract with potential extension depending on funding. Salary is £39,000–£46,500 per annum at SC6 and £47,450–£52,560 per annum at SC5, depending on qualifications and experience. Candidates able to evidence their PhD certificate at appointment are guaranteed a starting salary of £40,100; those awaiting confirmation will start at £39,000 until evidence is provided.
What's required
Applicants must have a PhD in a relevant quantitative discipline and strong expertise in at least one of mechanistic modelling, AI/ML or computational biology. Strong programming skills and a record of high-quality computational research are essential, as is the ability to work across disciplinary boundaries. Experience with hybrid modelling, Digital Twins, omics or single-cell data, or scientific machine learning is advantageous. Senior-level appointment additionally requires substantial postdoctoral or equivalent research experience, scientific independence, a publication track record, intellectual leadership of research workstreams, mentoring, and contributions to grant development or major collaborative outputs.
How to apply
Apply through the Earlham Institute vacancy page. Download, save and complete the application form in Microsoft Word, or submit a CV containing all information requested in the application form.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.