76 to 95 of 95 Ontologies Jobs

public sector) Embed client strategy and technical teams Stretching the frontier: hybrid KG + AI, graph + reasoning + M 🛠 Responsibilities Lead KG schema & ontology design across domains (assets, risk, supply chain, compliance) Build ingestion pipelines (ETL/streaming/CDC) and entity resolution for graph population Author complex queries …/AI concepts to non-technical audiences ✅ Nice-to-Have/Bonus Assets Experience with GraphRAG or KG-backed LLM retrieval Semantic web/ontology skills (RDF/OWL/SHACL) Prior consulting or client delivery background Graph visualization/UI experience (Linkurious, Bloom, Ogma) Graph DB certifications (Neo4j, Stardog ...

Senior Data Architect - Data Platform - Data Modeling - MDM - Data Management - Azure - Databricks As a Senior Data Architect, you will align the organisation's data architecture with its overall data strategy, establishing robust standards, governance and ...

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 ...

integrate emerging technologies into the team’s roadmap. Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems. 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 ...

foundations 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 domainsAlign data models with industry standards including TM Forum Open APIs, SID/eTOM, Open Digital … Architecture, YANG/NETCONF, and TOSCADrive adoption of ontology models across product teams as the semantic foundation for data exchange, AI training, and digital twin deploymentDevelop and lead the data fabric product architecture, including federated access, streaming pipelines, virtualization, metadata management, and lineage trackingTranslate data architecture vision into scalable, cloud ...

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 ...

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 ...

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 modelsEstablish ...

integrate emerging technologies into the team’s roadmap.Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems.Domain & Research IntegrationCollaborate 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, clinical … Computer Science, Data Science, Machine Learning, or a related fieldExperience 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 practicesFamiliarity with data visualization and analytical tooling (e.g., Tableau, Power ...

Data Modeller to help shape how HSBC defines, organises and connects business terms across the Group. You’ll 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 … reusable“Join the dots” across teams/domains to help build a shared semantic layer that supports cross-boundary understanding and consistencyContribute to ontology development (the layer between taxonomies) to enable AI to query and reason across multiple teams, products and datasets - turning terminology into a connected, machine-interpretable knowledge ...

science, including literature searching, content analysis, and knowledge synthesisProven ability to translate scientific and business questions into effective search and analysis techniquesFamiliarity with metadata, ontologies, and FAIR data principles for structuring scientific contentWorking knowledge of AI capabilities related to content analysis, such as large language models (LLMs), semantic technologies … cross-functional teamsNice to Have Skills:Practical experience in evaluating, piloting, or advising on AI-driven content toolsKnowledge of data visualization, knowledge graphs, and ontology managementFamiliarity with Python, AI frameworks, and prompt engineering techniques for NLP applicationsExperience with scientific communication tools and knowledge mappingPreferred Education and Experience:Bachelor ...

stronger cross-sell. Deliver in stages, proving value within 90 days, with reporting continuity guaranteed throughout. Master Data & Shared Definitions:Define and maintain the ontologies, taxonomies, and reference data that QIMA's systems currently define differently. Sequence the work by business urgency and risk, not by theoretical completeness. Name … sentence, what business outcome it unlocks - and you say no to the ones that can't. Data Governance & MDM:Hands-on experience defining data ontologies, taxonomies, master data strategies, and data contracts, taking an organization from fragmented, system-specific definitions to one shared standard. Cross-Functional Leadership & Influence:Strong track ...

clients to understand their business challenges, assess their knowledge landscape, and design production-ready solutions leveraging knowledge graphs, contextual data platforms, graph databases, GraphRAG, ontologies, and semantic technologies.Key ResponsibilitiesEngage with customers to identify business challenges that can be solved through contextual AI and knowledge-driven architectures.Assess enterprise knowledge assets, structured … deploy production-ready enterprise knowledge systems and rapid Proofs of Value (PoVs).Architect enterprise knowledge solutions using knowledge graphs, graph databases, semantic layers, ontologies, metadata management, and contextual data platforms.Design GraphRAG, Hybrid RAG, Agentic RAG, and contextual retrieval architectures to improve AI reasoning, explainability, and accuracy.Develop scalable ontologies, taxonomies, semantic ...

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 ...

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. Design, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches. Contribute to the development … 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 ...

year. In addition, ChEBI underpins many of the key global biological databases upon which researchers in the biosciences are increasingly reliant such as Gene Ontology (GO), Rhea, UniProtKB, IEDB, Reactome, MetaboLights, SwissLipids, and BioModels. The ChEBI database and ontology is a fundamental component of the global bioscience infrastructure, recognised … Chemical Biology Services team leader, the job responsibilities will include: Curation of entries into ChEBI, paying particular attention to chemical structures and the ChEBI ontology, to ensure the delivery of high quality data Monitoring ChEBIs monthly release process and liaising with technical/software colleagues if problems arise. Monitoring daily ...

frameworks and 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 SystemsDesign, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.Contribute … assistants, agentic workflows, or conversational AI applicationsExperience working on search, ranking, recommendation, or retrieval systemsFamiliarity with scientific, biomedical, or scholarly datasetsExperience with knowledge graphs, ontologies, or semantic enrichment systemsExposure to production ML systems and MLOps practicesAcademic or industry research experience in NLP, information retrieval, search, or generative AIExperience working ...

function. The Head of AI is responsible for building and leading a team that builds production systems handling unstructured clinical text, structured knowledge (ontologies and graphs), and generative AI. Dyad has a learning and teaching culture and the candidate for the role should be as comfortable coming up with accessible … frameworks for: Hallucination detection Precision and recall of extracted clinical concepts Regression testing across model updates Implement structured output approaches (e.g. schema-constrained generation, ontology-driven formats). Design iterative feedback loops, including human-in-the-loop review where appropriate. Ensure measurable improvements in grounding, explainability, and reliability over time. ...

Capgemini is seeking a Senior Semantic Governance Managing Consultant to define and govern enterprise ontologies, data standards, and semantic models. You will lead workshops with business SMEs, engage executives, and drive reuse across complex client environments. The role demands extensive ontology engineering expertise and hands-on knowledge of semantic technologies. ...

define, govern and industrialise enterprise semantic assets across data standards, controlled vocabularies, data contracts and knowledge graph implementations. The role requires deep expertise in ontology engineering, semantic technologies and knowledge representation, with the ability to engage senior stakeholders and drive consensus across business and technology teams. #J-18808-Ljbffr ...