Knowledge Graph and Ontology Specialist in Sheffield

The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.

We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more.

Overview

Are you an experienced knowledge engineer who enjoys solving complex data challenges? We have an exciting opportunity for you to join us as a Knowledge Graph and Ontology Specialist and build the semantic foundations for the future of industrial data.

You will join the AMRC at the University of Sheffield, as part of a growing interoperability team currently funded through the leadership of a UKRI Future Leadership Fellow. We are tackling critical barriers of system interoperability preventing organisations from leveraging the benefits of leading-edge technology, such as digital twins and AI, by unifying the current siloed infrastructures to drive industrial adoption. While the wider project focuses on accelerating industrial interoperability approaches, this role is dedicated entirely to the knowledge graph engineering and ontological understanding underpinning its success.

As a specialist, you will design and develop semantic architectures to make industrial data understandable, interoperable, and queryable. With 2-3 years of experience in knowledge engineering or conceptual modelling, you will establish information pipelines to extract semantic structure from information sources and apply advanced conceptual frameworks (including 3D vs. 4D approaches) to accurately capture complex engineering lifecycles.

Main duties and responsibilities

• Design, build, and maintain formal, machine-readable ontologies (e.g., using UML, RDF(S), SHACL, OWL) to support knowledge representation across multiple high-impact industrially-focused innovation projects.
• Apply advanced modelling paradigms, explicitly determining the appropriate use of 3D (endurantist/spatial) versus 4D (perdurantist/spatiotemporal) data modelling approaches to capture the state and lifecycle of engineering and research entities.
• Clearly document and differentiate the use of semantic technologies from primitive data dictionaries and taxonomies through to formal ontologies and logic across the project's infrastructure, ensuring the right tool is used for the right semantic requirement.
• Work closely with end users, software engineering and data scientists to ensure that all semantic models are FAIR (Findable, Accessible, Interoperable, and Reusable).
• Collaborate with the senior technical fellow, industry partners, and domain experts to extract implicit domain knowledge into explicit, rigorous conceptual models.
• Design the high-level semantic strategy and lifecycle management for the project's knowledge graphs and data schemas.
• Lead the writing of technical documentation, ontology release notes, and contribute to the dissemination of the project's ontological approach.
• Provide dissemination and mentorship to research teams on the importance of robust knowledge graph development and the practical differences between different semantic approaches (taxonomies vs ontologies).
• Organise technical alignment meetings and supervise/mentor junior staff.
• Make ethical decisions in your role, embedding the University's sustainability strategy into your working activities wherever possible.
• Carry out other duties, commensurate with the grade and remit of the post.

Person Specification

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and are respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply.

Criteria

• Bachelor's or master's degree in Information Science, Computer Science, Philosophy (with a focus on formal logic/ontology), Systems Engineering, or a related area, coupled with 2-3 years of practical knowledge graph and ontology experience.
• Working knowledge of foundational upper ontologies (e.g., BORO, HQDM, IES, ISO 15926, BFO, UFO, SUMO, DOLCE) and a demonstrable understanding of 4D (perdurantist/spatiotemporal) vs. 3D (endurantist/spatial) modelling methods in extending domain ontologies.
• Deep, practical understanding of the distinctions, limitations, and appropriate applications of formal ontologies versus data dictionaries, vocabularies, and taxonomies.
• Experience with semantic web technologies (RDF(S), OWL, SPARQL, SHACL), standard conceptual modelling languages (e.g., UML or similar) and linked data formats (e.g. Turtle).
• Practical experience with ontology authoring tools and workflows (e.g., Sparx Enterprise Architect, Protégé) and familiarity with ontology design patterns and common anti-patterns.
• Working knowledge and understanding of the differences between graph database technologies (e.g., Neo4j, GraphDB, RDFox) and experience building and managing knowledge graphs that integrate data from multiple sources.
• Experience translating raw or semi-structured engineering data into structured semantic models, with an understanding of data pipeline or ETL fundamentals.
• Ability to work in an interdisciplinary environment, interviewing domain experts to translate complex subject matter into formal logic and structured models.
• Effective communication skills, both written and verbal, including the ability to explain highly abstract conceptual models to non-technical stakeholders.
• Ability to work effectively as part of an agile team (e.g. scrum, kanban) with a demonstrated capacity to operate independently, alongside excellent time, project management, and collaborative skills.
• Experience applying version control (e.g., Git), continuous integration, or open-source practices specifically tailored to ontology development, model lifecycle management, or semantic data collaboration.
• Background or exposure to advanced manufacturing, engineering, or industrial R&D environments.

Further Information

• Grade 7
• Work arrangement: Full-time
• Duration: Fixed term until 31st October 2029
• Line manager: Senior Technical Fellow in Interoperability
• Direct reports: None - with opportunity for supporting placements and graduate staff.

Right to work in the UK: If you do not currently hold the right to work in the UK, you can find more information here to help determine your visa eligibility.

We are committed to exploring flexible working opportunities which benefit the individual and University.

Next steps in the recruitment process: The selection process will consist of an in-person interview at Factory 2050, Sheffield consisting of: a short presentation from applicants, a series of questions from a panel, followed by a tour around the facility. We plan to let candidates know if they have progressed to the selection stage within two weeks of the closing date.

A minimum of 41 days annual leave including bank holiday and closure days (pro rata) with the ability to purchase more.

Flexible working opportunities, including hybrid working for some roles.

A wide range of discounts and rewards on shopping, eating out and travel.

A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women’s and Parent’s networks).

Recognition Awards to reward staff who go above and beyond in their role.

A commitment to your development access to learning and mentoring schemes; integrated with our Academic Career Pathways / Professional Services Shared Skills Framework.

A range of generous family-friendly policies paid time off for parenting and caring emergencies access to menopause support in the workplace paid time off and support for fertility treatment.

We are a Disability Confident Leader. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.

Criminal record: Possession of a criminal record is not an automatic bar to employment at the University of Sheffield. We recognise the value of steady employment in the rehabilitation process and examine each case in its own right.

We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience.