| Location: | Culham |
|---|---|
| Salary: | £56,596 (inclusive of Specialist Allowance) |
| Hours: | Full Time |
| Contract Type: | Permanent |
| Placed On: | 23rd December 2025 |
|---|---|
| Closes: | 20th January 2026 |
Senior Knowledge Engineer
Abingdon Rd, Culham, UK
Full-time
Salary: £56,596 (inclusive of Specialist Allowance)
We are seeking a Senior Knowledge Engineer to join our team, driving data-driven fusion energy research through advanced semantic technologies. You will develop and maintain ontologies and knowledge graphs that integrate experimental data, simulations, and scientific literature, enabling researchers to efficiently access and interpret complex datasets. The role involves responsibly applying generative AI tools, including large language models, to accelerate ontology development and knowledge graph creation while ensuring transparency, provenance, and quality. You will work across knowledge engineering, data integration, and applied AI, building scalable semantic systems, contributing to research strategy, supervising early-career researchers, leading small projects, and collaborating with scientists and engineers to ensure solutions meet evolving research and industry needs. Strong organisational and time-management skills, experience coordinating scientific or technical events, and excellent written and verbal communication are essential.
You will lead projects from inception to delivery, ensuring milestones, outputs, and budgets are met, while identifying new research and funding opportunities aligned with UKAEA’s semantic data strategy. The role requires practical expertise in designing modular, standards-aligned ontologies and scalable knowledge graphs, applying generative AI to enhance ontology creation, and enabling semantic interoperability through ontology alignment, vocabulary mapping, and automated workflows. You will work closely with scientists, engineers, and software teams, producing clear technical documentation and promoting best practices in knowledge engineering. Candidates should hold a PhD in Computer Science, AI, or a related field, or equivalent experience, with strong engineering skills, familiarity with semantic standards (e.g., Dublin Core, DCAT, PROV), and experience with tools such as Protégé, ROBOT, OWLAPI, Neo4j, or GraphDB. Demonstrated teamwork through projects, events, or co-authored outputs is also required.
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