18 of 18 Ontologies Jobs in England

streaming responses, async inference jobs, and robust error/retry semantics. Palantir Foundry Integration Work with Palantir Foundry to build and maintain data pipelines, ontologies, and integrations that connect backend services to Foundry-based analytics and workflows. Leverage Foundry's APIs and tooling to support data modelling, transformation, and secure ...

using modern Azure technologies. Optimising data pipelines to ensure high levels of performance, data quality, consistency, and availability. Supporting the development of an enterprise ontology model to improve understanding and relationships across data domains. YOUR SKILLS AND EXPERIENCE: You will bring strong capability in: Microsoft Azure data engineering technologies. Designing ...

complex, ambiguous environments. * A strategic mindset combined with the ability to drive practical outcomes. Desirable Experience * Cloud migration and cloud-native data architecture. * Ontologies, semantic modelling or knowledge graphs. * AI-enabled data architectures and emerging technologies. * Experience developing enterprise data standards and frameworks. DV Clearance Eligibility Requirements * UK residency history ...

generation Developing intelligent retrieval, ranking, recommendation and decision-support systems Applying semantic, vector and hybrid search techniques across large-scale datasets Integrating metadata, taxonomies, ontologies and structured knowledge into AI workflows Developing robust LLM and AI evaluation frameworks , experimentation methodologies and monitoring Improving the quality, reliability, trust and performance ...

evidence-grounded insight generation. Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks and AI techniques. Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows. Establish robust evaluation, experimentation, and monitoring frameworks to ensure quality, trust, performance, and reliability. Write production-ready Python ...

programmes , from conceptual modelling through logical/physical layers, tied directly to business priorities. Develop a unified language for data -dictionaries, vocabularies, taxonomies and ontologies that allow teams to interpret data consistently. Shape data and analytics architectures collaboratively with solution and enterprise architects. Act as a trusted advisor to senior ...

discovery, knowledge extraction, decision support, and intelligent content understanding. Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature ...

other cloud-native platforms. Event-driven architectures and asynchronous messaging. Istio, mTLS or service mesh technologies. Knowledge of semantic search, knowledge graphs or ontology-based solutions. Mandatory Requirements Current DV Security Clearance. Ability to work onsite at an MOD location in London four days per week. Previous experience delivering within ...

scalability of Neo4j environments. Driving graph quality initiatives, confidence scoring and automated data validation processes. Collaborating with architects, engineers and stakeholders to evolve ontology and schema frameworks. We're looking for Strong commercial experience with Neo4j in large-scale enterprise environments. Advanced Cypher query development and optimisation skills. Proven experience ...

ambiguity and take responsibility for the outcome. Strong experience with Databricks and Azure OpenAI, which underpin much of our delivery. Nice to have Ontology, knowledge graph or semantic layer experience. Delivery experience in pharma or CPG. Practical experience designing systems around EU AI Act requirements. Multilingual AI systems in production. ...

Graph-structured data, designing and utilising relational and graph databases, and knowledge of graph algorithms. Desirable Knowledge, Skills and Experience: Familiarity with knowledge representation, ontology design and semantic or LLM based reasoning Experience with one or more graph machine learning packages (PyTorch-Geometric, PyKeen etc.) and knowledge graph toolkits (Neo4j ...

100. Talk to customers and partners to find the problem worth solving, not just to validate a solution. Own the Global Product Graph — the ontology, the data, and the workflows that keep it accurate. Develop the insurance intelligence on top of it: product scoring, compliance evaluations, and what "good" means ...

Builds and maintains APIs/integration layers exposing graph data to downstream consumers (including the chatbot) Collaborates with the Knowledge Graph Architect to implement ontology, knowledge and schema changes as code Supports performance tuning, indexing, and scaling of the Neo4j instance Automates data refresh and synchronisation processes between source systems ...

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 ...

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 ...

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 ...

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 ...

platform leadership role with a governance mandate, not a governance role at platform distance. What you will own The enterprise knowledge graph: ontology and schema design, the pipelines that build and refresh it from production data, and graph retrieval as a first-class platform capability for the product lines … becomes the training and evaluation datasets behind the LLMs and SLMs we tune ourselves What you will need Graph engineering depth: you have designed ontologies and graph schemas and operated production graph systems (Neo4j or comparable), including graph retrieval for AI workloads RAG in production: you have built and optimised ...