Senior) Research Software Engineer - AI integrated Digital Twins of system

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

Job Title (Senior) Research Software Engineer - AI integrated Digital Twins of living system Post Number 1006211 Closing Date 2 Dec 2026 Grade SC6/SC5 Starting Salary Salary: £39,000-£52,560

Hours per week 37 Months Duration 24

Applications are invited for a (Senior) Research Software Engineer to join Dr Rahuman Sheriff's group at the Earlham Institute.

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.

Internal:
Sheriff, and other group members

External:interact with visitors (Dr Tung Nguyen and Dr TJ Sego)

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 Bio Models 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 Bio Models, 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.