Main Purpose of the Job

The post holder will conduct primary research in the AI integrated Digital Twins Group to develop predictive, mechanistically interpretable models of living systems by integrating systems biology, artificial intelligence and high-dimensional biological data.

The role will develop and apply biological Digital Twin methodologies across questions relevant to the Earlham Institute's research programmes. Digital Twins will be purpose-built predictive models rather than comprehensive replicas, combining mechanistic models with AI/ML and multimodal data to simulate biological states and responses to genetic, environmental or experimental perturbations.

This is a core-funded group position with substantial scope for independent methodological research. The post holder will work across scales and biological systems, contribute to the group's longer-term Digital Twin methodology, and collaborate with EI researchers and technology platforms in genomics, single-cell and spatial biology, engineering biology, data science and research computing.

Appointment will be made at SC6 (Postdoctoral Research Scientist) or SC5 (Senior Postdoctoral Research Scientist), according to the candidate's experience and evidence against the published criteria.

Key Relationships

The role is core funded and will interact broadly with EI's research programmes and technology platforms, providing opportunities to work with genomics, single-cell and spatial data, engineering biology and advanced research computing.

Main Activities & Responsibilities

Percentage

Develop new predictive systems-biology and Digital Twin methodologies combining mechanistic modelling, AI/ML and biological data; investigate model personalisation, hybrid architectures, perturbation prediction, uncertainty and counterfactual simulation.

35

Construct, parameterise, train and validate predictive models using bulk, single-cell, spatial and other multimodal biological datasets, with applications across EI's plant, microbial and mammalian research where scientifically appropriate.

25

Develop and evaluate hybrid mechanistic-AI approaches, including learned components within mechanistic models, AI-assisted parameter/state inference, surrogate modelling and mechanisms for connecting data-driven predictions with executable biological models.

20

Lead or contribute to high-quality publications, open models, benchmarks and reproducible workflows; collaborate across EI and with external partners and contribute to competitive research proposals.

15

Mentoring, presentations, preparing grant applications, training and other duties commensurate with the role.

5

For appointment at SC5, take operational leadership of selected research initiatives in the Sheriff Group. 

For appointment at SC5, participate in supervision of students, other team members, leading projects and collaborations, and leading on the preparation of data/information for grant proposals

For appointment at SC5, contribute to the smooth running of the group, including budget management, and the effective use of group resources, encouraging scientific excellence and develop personal leadership skills. 

As agreed with line manager, any other duties commensurate with the nature of the role

Education & Qualifications

Requirement

Importance

PhD awarded, or expected within six months, in computational/systems biology, bioinformatics, AI/ML, applied mathematics, physics, engineering, computer science or a related quantitative discipline.

Essential

Specialist Knowledge & Skills

Requirement

Importance

Strong expertise in at least one of the following areas: mechanistic/systems-biology modelling; AI/ML for biological data; computational biology/bioinformatics, with the ability and motivation to work across these areas

Essential

Strong scientific programming skills, preferably Python, with experience developing reproducible computational research workflows

Essential

Demonstrate very high motivation in the project and describe how their skills and expertise align with the aims of the post to make the project successful and support their career progression

Essential

Understanding of quantitative model validation, uncertainty, generalisation and biological interpretation

Essential

Experience in analysing high-dimensional biological data such as genomics, transcriptomics, single-cell, spatial or other multi-omics data

Essential

Knowledge of hybrid mechanistic-AI modelling, scientific machine learning or biological Digital Twins

Desirable

Experience with ODE, stochastic, logical, constraint-based, agent-based or multiscale modelling

Desirable

Experience with deep learning frameworks such as PyTorch/JAX/TensorFlow

Desirable

Substantial postdoctoral or equivalent research experience demonstrating scientific independence and track record of publications (essential for SC5)

Desirable

Relevant Experience

Requirement

Importance

Evidence of high-quality computational research outputs commensurate with career stage, such as publications, open-source software, models, datasets or benchmarks

Essential

Experience developing and validating original computational methods or models rather than solely applying standard pipelines

Essential

Experience collaborating across disciplinary boundaries

Essential

Evidence of intellectual leadership of research workstreams, mentoring and contribution to grant development or major collaborative outputs (essential for SC5)

Desirable

Interpersonal & Communication Skills

Requirement

Importance

Ability to communicate complex quantitative concepts clearly to computational and experimental researchers

Essential

Ability to work independently and collaboratively, manage priorities and use initiative

Essential

Good interpersonal skills, with the ability to work well as part of a team

Essential

Good communication skills, both written and verbal

Essential

Additional Requirements

Requirement

Importance

Attention to detail

Essential

Commitment to reproducible, open and responsible research

Essential

Willingness to undertake occasional national or international travel for collaborations and conferences

Essential

Willingness to embrace the expected values and behaviours of all staff at the Institute, ensuring it is a great place to work

Essential

Able to present a positive image of self and the Institute, promoting both the international reputation and public engagement aims of the Institute

Essential

Willingness to work outside standard working hours when required

Essential

Promotes equality and values diversity

Essential

Earlham Institute

About the Earlham Institute
The Earlham Institute harnesses the power of data-driven biology to accelerate solutions for health, biodiversity, and food security. Based at Norwich Research Park, the Earlham Institute is one of eight institutes strategically funded by BBSRC.

Our science combines world-class technology, interdisciplinary expertise, and training and development across genomics, engineering biology and data science, to decode the scale and complexity of living systems.

We believe we can achieve more if we work together. That's why we collaborate with the global science community and industry partners, while also inspiring the next generation of scientists and technical specialists.

Our Science
Earlham Institute scientists specialise in developing and testing the latest tools and approaches needed to decode living systems and make biological predictions.

We are home to state-of-the-art facilities and technology, creating a unique combination of expertise and infrastructure.

We have dedicated laboratories for genome sequencing, single-cell analysis, engineering biology, and large-scale automation; as well as one of the largest supercomputing facilities for life science research in Europe.

Our Advanced Training team also provides access to specialised scientific training to upskill the next generation of research and technical staff.

Our Culture
Our collegiate and innovative research environment comes with significant support, including a commitment to your professional development, research and administrative assistance, and opportunities to build collaborations with scientists and industry on the Norwich Research Park, across the UK, and internationally.

We are committed to building and maintaining a workplace that treats every individual with dignity and respect. By taking an active approach to fostering inclusivity, diversity, equality and accessibility, we empower our community to achieve more.

The Institute is also home to talented technical and operational staff, whose invaluable contributions enable our science to have the maximum impact. We aim to recognise, reward, and develop all staff and students so that every individual feels able to achieve their best with us.

We work hard to nurture an engaged and positive workplace, centred on core values that include openness, technical excellence, and collaboration. We attract staff from around the world who contribute to - and benefit from - an environment that enables them to deliver world-class science alongside a supportive and social community.

For more information about working at the Earlham Institute, please click here.

Further Information:

• Our Vision and Mission
• Our Strategy
• Our Culture
• Life at Earlham Institute

Department

Research Faculty

Group Details

The group develops predictive models and biological Digital Twins that combine mechanistic understanding, AI/ML and high-dimensional biological data. The programme aims to move beyond association-based prediction towards models that can represent biological processes, simulate perturbations and generate testable, interpretable predictions across living systems.

Living in Norfolk

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(Senior) Postdoctoral Research Scientist - AI Integrated Digital Twins

Applications are invited for a Postdoctoral Research Scientist (SC6) or Senior Postdoctoral Research Scientist (SC5) to join Dr Rahuman Sheriff's AI integrated Digital Twins Group in the Research Faculty of the Earlham Institute, based in Norwich, UK.

Background:

The group develops predictive models and biological Digital Twins that combine mechanistic understanding, AI/ML and high-dimensional biological data. The programme aims to move beyond association-based prediction towards models that can represent biological processes, simulate perturbations and generate testable, interpretable predictions across living systems.

The role is core funded and will interact broadly with EI's research programmes and technology platforms, providing opportunities to work with genomics, single-cell and spatial data, engineering biology and advanced research computing.

The role:

We are seeking an ambitious computational scientist to develop new methods for predictive systems biology and biological Digital Twins. You will combine 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 has 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 ideal candidate:

You will have a PhD in a relevant quantitative discipline and strong expertise in at least one of mechanistic modelling, AI/ML or computational biology, together with the ability to work across disciplinary boundaries. Strong programming and a record of high-quality computational research are essential. Experience with hybrid modelling, Digital Twins, omics/single-cell data or scientific machine learning would be advantageous.

Appointment will be made at SC6 or SC5 according to experience and evidence against the published criteria. For appointment at SC5, candidates will additionally be expected to demonstrate substantial postdoctoral or equivalent research experience demonstrating scientific independence and track record of publications and evidence of intellectual leadership of research workstreams, mentoring and contribution to grant development or major collaborative outputs. 

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 £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. 

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.

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 2 December 2026.