101 to 125 of 125 Ontologies Jobs in England

with AI, automation, and product innovation across the portfolio.**How you will make an impact:*** Define and own the canonical telco data model and ontology across network topology, service lifecycle, inventory, assurance, and OSS domains* Align data models with industry standards including TM Forum Open APIs, SID/eTOM, Open … Digital Architecture, YANG/NETCONF, and TOSCA* Drive adoption of ontology models across product teams as the semantic foundation for data exchange, AI training, and digital twin deployment* Develop and lead the data fabric product architecture, including federated access, streaming pipelines, virtualization, metadata management, and lineage tracking* Translate data architecture ...

complex modalities such as genomics, transcriptomics, imaging, clinical and real-world datasets. Partner with the Data Excellence community and IT to align on governance, ontologies, metadata harmonisation, stewardship and shared enterprise data foundations. Establish ways of working and coach other team members, onboarding, mentoring and technically leading data engineers … requirements, including versioning, reproducibility and tensor-based workflows for large-scale AI systems. Experience implementing data governance in practice, including metadata management, lineage, provenance, ontologies, cataloguing and FAIR principles and familiarity with Trusted Research Environments (TREs) and controlled-access research data environments. Strong collaboration and influencing skills across technical ...

team in London, London, City of (GB-LND), United Kingdom (GB).Job Title: Knowledge Graph ArchitectExperience: 10+ years (5+ years in Knowledge Graphs/Ontology Engineering)Role OverviewWe are looking for a Knowledge Graph Architect to lead the design and governance of enterprise knowledge graphs. This role will define … ontology, data model, and canonical vs. interpretive boundaries, enabling scalable, high-quality graph data for AI-driven use cases, including Graph RAG.The role also requires strong team leadership, including coaching, mentoring, and building internal capabilities. Key ResponsibilitiesArchitecture & DesignDefine node types, relationships, schemas, and property standardsDesign scalable and extensible graph data ...

into the team’s roadmap. Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems. Domain & Research Integration Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems. Incorporate structured data — including datasets, chemical entities, genes, drugs … Computer Science, Data Science, Machine Learning, or a related field Experience working with large‐scale datasets (scientific, biomedical, or enterprise data) Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef) Exposure to production ML systems and MLOps practices Familiarity with data visualization and analytical tooling (e.g., Tableau ...

into the team’s roadmap. Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems. Domain & Research Integration Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems. Incorporate structured data — including datasets, chemical entities, genes, drugs … Computer Science, Data Science, Machine Learning, or a related field Experience working with large-scale datasets (scientific, biomedical, or enterprise data) Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef) Exposure to production ML systems and MLOps practices Familiarity with data visualization and analytical tooling (e.g., Tableau ...

Accuracy: Serve as the crucial "human in the loop," auditing, fine‐tuning, and optimizing LLM‐generated classifications, descriptions, and data extractions. Architect the ETF Ontology: Build, refine, and maintain a single source of truth—our unified ETF taxonomy and ontology—to set the standard for asset class categorization. Ensure Uncompromising … Science, Data Analytics, or a related quantitative field. Bonus Points: Existing relationships with major financial market data vendors and direct experience building taxonomy/ontology frameworks. Salary Range: $80,000K/year - $90,000K/year USD Please note that the Salary Range included is a guideline only. The salary ...

integration infrastructure Reconcile and unify data from multiple, heterogeneous sources Develop flexible ways to model and interpret unfamiliar data Shape the semantic models and ontologies that give business data consistent meaning Design reliable, observable orchestration for complex data workflows Establish strong foundations for data quality, lineage and observability Embed permissions … ClickHouse or DuckDB Experience with distributed systems and third-party integrations A pragmatic mindset and a strong bias towards shipping Experience with semantic models, ontologies or knowledge graphs would be a bonus. You don’t need to meet all the requirements. We care more about what you’ve built ...

completeness. Focus on Material domains and future expansion to other scientific domainsDatabase Development and Maintenance: Contribute to the design and maintenance of our scientific ontology, ensuring efficient data storage, retrieval, domain coverage, and integration with our software platformPipeline Development: Implement ETL pipelines for ingesting, cleaning, and transforming scientific datasets from … analyse scientific data, identify trends, and develop predictive models for domain-relevant properties and behavioursOntology Development and Classification: Develop and maintain a comprehensive scientific ontology and classification system to enable efficient searching and filtering based on substance class, properties, and applicationsIntegration with Software Tools: Collaborate with software engineers to ensure ...

Group Business Glossary, Taxonomy of Business Terms, and Group Data Categories (high-level groupings of terms) Build high-quality glossaries, taxonomies and ontologies that create a shared semantic layer - so our data can be understood consistently and used by AI to answer questions across teams, faster and with more confidence … bring Is useful but not essential (tooling matters less than the modelling fundamentals) Demonstrable experience in business glossary curation, taxonomy design, and/or ontology modelling, with a clear understanding of how these enable AI and data interoperability With modelling and metadata practices; Collibra , with the ability to explain semantic ...

remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. … degree or equivalent, plus at least 4 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) solid experience in schema design, ontology management, and KG curation Proven experience in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with ...

remain at the forefront and drive innovation by applying these techniques to new business problems, use cases, and scenarios. You design, evaluate, and maintain ontologies, and establish the standards others follow. You justify the value to business and technology stakeholders, and construct the methodologies and data architectures that demonstrate it. … degree or equivalent, plus at least 4 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) solid experience in schema design, ontology management, and KG curation Proven experience in designing and developing KG solutions and graph-based ML models (functional + technical) Experience with ...

user stories, and acceptance criteria. Data & Workflow Mapping: Documenting current-state data flows across command nodes and defining target-state fused data workflows. Palantir Ontology Alignment: Working with Data Specialists to map real-world military assets, events, and relationships into the Palantir object model. Traceability & Compliance: Maintaining traceability between operational … Stories, Acceptance Criteria (Gherkin), Gap Analysis, Process Mapping, Target Operating Model (TOM). Data & Domain: Data Dictionary Creation, Operational Workflows, C2 (Command & Control) Workflows, Ontology Alignment, Data Traceability. Stakeholder & Governance: Military Stakeholder Engagement, Subject Matter Expert (SME) Facilitation, MoD Procurement Awareness, DefStan Compliance. Important Information Start Date: ASAP Security Requirements ...

customer's business - P&L drivers, operating model, competitive pressures, and regulatory environment. Speaks insurance fluently, or has fluency in financial services technology. Insurance Ontology and AutonomousInsurer thesis: Carries the Sapiens point of view into every engagement - articulating why a shared data model across the insurance value chain creates structural … task. Leads the full talent lifecycle with candour and integrity. Sapiens ambassadorship: Carries the Sapiens point of view into customer environments. Knows the Insurance Ontology argument, the AutonomousInsurer thesis, and the AI moat – and can hold them in a room. Leads the Programme's PM team, setting standards and driving ...

Описание Spectrum is a JetBrains startup incubator project that collects data from code, documentation, and issues, organizing it into a unified ontology for AI agents to search and reason over. It aims to provide a living specification and a single source of truth for product and architectural knowledge in software … ability to explain complex technical concepts to diverse audiences; Proficiency in English, both written and verbal; Nice to have: Kotlin knowledge, experience with ontologies, knowledge graphs or graph-based reasoning, early-stage startup experience, strategic thinking about product-led AI, background in code analysis, developer tools or software engineering research ...

tool interfaces, and integration patterns that enable AI capabilities to interact effectively with MES business processes. Leading the platform's approach to data modelling, ontology strategy, semantic understanding, and business context required for AI-driven experiences. Providing architectural leadership across multiple engineering teams delivering AI, Integration, IoT, Connected Worker … software products. Experience designing APIs, service contracts, and software architectures. Experience with cloud-native application development and modern SaaS architectures. Experience with semantic modelling, ontologies, knowledge graphs, or domain-driven modelling approaches used to represent complex business domains. Strong understanding of software architecture, security, scalability, reliability, and observability. Excellent C# ...

define entities attributes relationships cardinality Experience modelling complex domains with many-to-many relationships hierarchical structures rule-based logic Experience in knowledge graph modelling ontology tools (e.g. Protégé) graph concepts (nodes, edges, traversal) Experience in regulated environments (government, finance) Conduct knowledge discovery across the organisation, working with stakeholders to understand … domains Translate unstructured understanding into structured artefacts (models, diagrams, definitions) Develop conceptual and logical data models to underpin knowledge graphs Support the creation of ontology and taxonomy models Enable downstream teams to build knowledge graphs RAG pipelines AI retrieval systems Public sector background Location: Remote with key meetings in Manchester ...

broader solutioning ecosystem. This role sets the technical and operating direction for software developers, UX developers and designers, tools application developers, enterprise data architecture, ontology development, and deployment/testing capabilities. Operating as the leadership anchor for the tools team, the role promotes modern software development practices, strong product … through transformation Accountabilities Lead and develop a multidisciplinary tools organization spanning software developers, UX developers and designers, tools application developers, enterprise data architecture, data ontology resources, and deployment/testing roles. Define and execute the tools team operating model, engineering standards, and delivery practices needed to build scalable, secure, maintainable ...

Building services and APIs that expose contextual manufacturing information for AI-enabled applications and workflows. Working closely with the Principal AI Lead to define ontology strategies, semantic standards, and modelling approaches. Designing scalable architectures for ingesting, processing, and modelling industrial IoT and telemetry data. Supporting AI reasoning, diagnostics, automation … models. Strong understanding of relational databases, data modelling, and information architecture principles. Experience working with cloud-native development and modern SaaS architectures. Understanding of ontology design, semantic modelling, knowledge representation, or domain-driven design concepts. Strong understanding of software architecture, scalability, reliability, and observability principles. Demonstrated ability to solve complex ...

contribute recommendations for experimentation and adoption. Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts. Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows. Search, Retrieval & RAG Systems Design, develop, and optimize search and retrieval pipelines , including lexical, vector, and hybrid retrieval approaches. … conversational AI applications Experience working on search, ranking, recommendation, or retrieval systems Familiarity with scientific, biomedical, or scholarly datasets Experience with knowledge graphs, ontologies, or semantic enrichment systems Exposure to production ML systems and MLOps practices Academic or industry research experience in NLP, information retrieval, search, or generative AI Experience ...

data map measured bioactivity data from the scientific literature to other biological entities (proteins, cell-lines etc) using a variety of bioinformatics resources and ontologies work collaboratively with other EMBL-EBI teams to integrate ChEMBL data into their resources and vice versa proactively identify new data types and additional annotations … skills (both verbal and presentational) You might also have Prior experience of biological data curation and knowledge of bioinformatics databases Some knowledge of biological ontologies Experience of working in a drug discovery environment Experience of working with and manipulating file formats such as FASTA, Excel, XML, OBO and familiarity with ...

University of Sheffield invites applications for a Knowledge Graph and Ontology Specialist within AMRC. You will design, build and maintain ontologies, apply 3D/4D modelling, and collaborate with engineers and data scientists to ensure FAIR semantic models. We seek candidates with strong background in RDF(S)/OWL, Protégé ...

University of Sheffield is seeking an experienced Knowledge Graph and Ontology Specialist to build the semantic foundations for the future of industrial data. We offer flexible working opportunities and a commitment to development and wellbeing, with a benefits package including generous annual leave and pension schemes. In this role … will tackle complex data challenges, design ontologies, and enable scalable data integration across multiple systems. #J-18808-Ljbffr ...

University of Sheffield invites applications for a Knowledge Graph and Ontology Specialist within the Advanced Manufacturing Research Centre. You will design and implement semantic architectures to make industrial data interoperable, understandable and queryable, guiding knowledge graph lifecycles and ontological standards across multiple projects. With 2-3 years in knowledge engineering … will articulate 4D vs 3D modelling decisions, document ontology releases, and mentor junior staff #J-18808-Ljbffr ...

ecosystems. Establish AI quality engineering practices, including agent evaluation frameworks, synthetic data strategies and agentic testing methodologies. Design and scale enterprise knowledge architectures, ontologies and retrieval systems that enable trustworthy, context-aware AI experiences. Work model We believe hybrid work is the way forward as we strive to provide flexibility … such as Copilot Studio or Agentforce, and MCP/A2A agent protocols. Expertise in RAG-at-scale and grounding strategy, plus knowledge graph and ontology engineering. Agentic test-framework design experience together with AI security and access controls. These will help you succeed AI-native solution architecture expertise paired with ...

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. #J-18808-Ljbffr ...