Main Purpose of the Job

The post holder will be a research-active software engineer in the Sheriff Group, designing and building reusable software infrastructure that connects mechanistic models, AI/ML models, biological datasets and scalable compute into robust Digital Twin research systems.

The role is not conventional IT support. The post holder will work alongside research scientists to translate new modelling and AI/ML methods into high-quality, tested and reusable research software, including model/data interfaces, AI model training and inference pipelines, workflow execution, simulation and optimisation pipelines, model serving, provenance, APIs and reproducible deployment.

The software will support heterogeneous modelling frameworks and hybrid mechanistic-AI workflows, enabling researchers to construct, parameterise, train, simulate, validate and compare biological models across local, HPC, GPU and cloud environments. This is a research software engineering position with substantial scope for hands-on AI/ML implementation, including integration and optimisation of modern machine-learning models and GPU-accelerated inference and execution.

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

Key Relationships

Internal: Sheriff, and other group members
External: interact with visitors (Dr Tung Nguyen and Dr TJ Sego)
 

Main Activities & Responsibilities

Percentage

Design and implement the software architecture for predictive systems-biology and Digital Twin workflows, connecting mechanistic simulators, AI/ML components, biological data, optimisation/inference methods and compute infrastructure.

25

Develop robust Python-based research software and implement AI/ML models and workflows, including training and inference pipelines, model serving, APIs and data/model interfaces; support reproducible execution across local, HPC, GPU and cloud environments.

20

Build infrastructure for hybrid mechanistic-AI modelling, including simulation/training pipelines, model exchange, experiment configuration, provenance, versioning and reproducible evaluation.

20

Apply professional software engineering practices including version control, testing, code review, CI/CD, containers, documentation, packaging, performance profiling and release management; at SC5 lead architecture, engineering standards and technical risk management.

15

Maintain and extend the BioModels repository and associated services, including deployment, APIs, databases, model ingestion and dissemination workflows, standards support, testing and operational reliability. Develop infrastructure for secure, scalable and reproducible online execution of computational and AI/ML models linked to BioModels, including cloud/HPC/GPU-backed execution.

10

Contribute to open-source releases, technical/research publications, collaborations, mentoring and future grant applications.

10

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

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

Education & Qualifications

Requirement

Importance

Degree in computer science, software engineering, scientific computing, AI, computational biology or a related discipline, or equivalent professional/research experience.

Essential

PhD or equivalent research experience in a relevant quantitative field.

Desirable

Specialist Knowledge & Skills

Requirement

Importance

Strong hands-on software engineering skills and proficiency in Python.

Essential

Strong motivation in the project and demonstration how their skills and expertise align with the aims at posts to make the project successful and support their career progression.

Essential

Strong knowledge of version control, testing, documentation and maintainable software design.

Essential

Experience with APIs, data formats, databases and/or workflow systems used in scientific or data-intensive software.

Essential

Experience with Linux and reproducible deployment using containers such as Docker/Apptainer.

Essential

Knowledge of secure online model-execution, inference or simulation services, including containerised execution and job orchestration.

Desirable

Hands-on knowledge of machine-learning frameworks such as PyTorch, JAX or TensorFlow and model training, inference and/or model-serving workflows.

Desirable

Knowledge of scientific modelling/simulation frameworks, numerical computing or systems biology.

Desirable

Knowledge of FAIR/reproducible research standards and scientific model formats such as SBML, SED-ML, ONNX or related standards.

Desirable

Relevant Experience

Requirement

Importance

Evidence of high-quality technical outputs such as open-source software, widely used research tools, technical demonstrators, packages, benchmarks or publications.

Essential

Experience developing complex research software, scientific platforms, data-intensive infrastructure or AI/ML systems.

Essential

Experience working directly with researchers to turn evolving scientific requirements into usable software.

Essential

Evidence of mentoring developers or researchers with limited supervision (essential for SC5).

Desirable

Experience maintaining, extending or operating a production research software platform, scientific repository or community-facing data/model resource.

Desirable

Evidence of owning software architecture/roadmaps, setting engineering standards and managing technical risk (essential for SC5).

Desirable

Interpersonal & Communication Skills

Requirement

Importance

Ability to communicate technical design decisions clearly to software engineers and research scientists.

Essential

Ability to work collaboratively in an interdisciplinary research environment while taking ownership of technical delivery.

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

Promotes equality and values diversity.

Essential

Commitment to robust, reproducible and responsible research software.

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

Attention to detail

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 systems-biology models and biological Digital Twins that combine mechanistic modelling, AI/ML and high-dimensional biological data. These approaches require robust software capable of connecting heterogeneous models and datasets with simulation, AI model training and inference, optimisation, model serving and scalable computing.
 

Living in Norfolk

• Visit Norfolk
• Schools in Norfolk
• Childcare in Norfolk

(Senior) Research Software Engineer- AI integrated Digial Twins of living system

Applications are invited for a Research Software Engineer (SC6) or Senior Research Software Engineer (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 systems-biology models and biological Digital Twins that combine mechanistic modelling, AI/ML and high-dimensional biological data. These approaches require robust software capable of connecting heterogeneous models and datasets with simulation, AI model training and inference, optimisation, model serving and scalable computing.

The position is core funded and will work across the group's research programme while collaborating with EI's research e-infrastructure and computational and biological research teams. A key component will be supporting the maintenance and continued development of BioModels and extending its infrastructure for emerging computational modelling, AI/ML and Digital Twin use cases.

The role:

We are seeking a research-focused software engineer with a strong interest in AI/ML to design and build reusable infrastructure for biological Digital Twins. You will connect mechanistic simulators, AI/ML models, omics and multimodal datasets, inference and optimisation tools, and HPC/GPU/cloud resources into robust and reproducible scientific workflows. This is an RSE position with substantial scope for hands-on AI/ML model implementation and engineering.

The work will include software architecture, Python libraries and APIs, implementation of AI/ML training and inference pipelines, model serving, model/data interfaces, workflow execution, provenance and versioning, containers, automated testing and CI/CD, performance optimisation and open-source releases. You will work directly with scientists developing new AI/ML and hybrid mechanistic-AI methods and help turn research prototypes into reliable, scalable tools. You will also contribute to the engineering and operation of BioModels repository, maintaining existing services while developing new APIs and execution workflows, including secure and reproducible online execution of computational and AI/ML models using cloud, HPC and GPU resources.

The ideal candidate:

You will have strong software engineering and Python skills, experience building complex scientific, AI or data-intensive software, and a good understanding of professional development practices including testing, version control and documentation. Hands-on experience with ML frameworks, AI model implementation, HPC/GPU environments, cloud deployment, model serving, scientific modelling, workflow systems or FAIR model/data standards would be advantageous. Experience maintaining a production scientific platform or repository would also be valuable.

Appointment will be made at SC6 or SC5 according to experience and evidence against the published criteria. SC5 candidates will additionally demonstrate ownership of software architecture and technical roadmaps, leadership of engineering standards and mentoring or coordination of other developers/researchers.

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 for the SC6 level post, and £47,450 to £52,560 per annum for candidates who meet the SC5 level criteria. 

Depending on the level of the appointment, this role may not meet the full salary requirements set by UKVI to allow for Skilled Worker visa sponsorship. However, some individuals may still be eligible for visa sponsorship depending on their personal circumstances. If you require visa sponsorship, please visit the GOV.uk website to find out if you qualify before applying. Please note, the occupation code for this role is 2134, which is not on the immigration salary list.

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.