Senior Research Scientist ££65,000 GBP Hybrid WORKING Location: United Kingdom (East of England - Chelmsford) Type: Permanent A leading organisation at the forefront of AI and data innovation is seeking an experienced Senior Research Scientist to head its Knowledge and Semantics group, which operates within a wider capability focused on Data and Decision Support. This capability includes teams specialising in reinforcement learning, natural language processing (NLP), knowledge graphs, large language models (LLMs), computer vision, and AI applications for RF, electronic warfare, sonar, and acoustics. About the Role The Team Lead will guide a group of researchers and engineers working in NLP, LLM applications, text mining, knowledge graphs, and graph-based machine learning. The ideal candidate will be a skilled technical leader with a clear vision for applying machine learning to real-world challenges, particularly within the defence, security, and commercial domains. This is a highly collaborative role, offering the opportunity to work in multi-disciplinary teams and contribute to a broad portfolio of AI/ML projects. It also provides scope to engage with academic institutions, SMEs, and technical partners, while shaping future research directions. Key Responsibilities: Lead and deliver research projects in NLP, knowledge representation, and machine learning, often in collaboration with leading UK universities. Direct technical teams, ensuring timely delivery of high-quality technical outputs including reports, demonstrators, and proposals. Develop and prototype innovative AI/ML solutions with practical applications. Support the generation of new business through the preparation of successful R&D proposals. Present technical work effectively to both specialist and non-specialist audiences. Take ownership of technical challenges and drive projects to completion. Essential Skills and Experience: PhD in a relevant discipline, with a minimum of four years' post-doctoral experience. Proven leadership of research and development teams, typically with five or more members. Strong record in securing and delivering funded R&D projects. Proficient programming skills in Python, with extensive experience in ML development using libraries and toolkits. Familiarity with at least one major ML framework such as TensorFlow or PyTorch. Desirable Technical Expertise: Candidates should demonstrate expertise (through publications, industrial applications, or open-source contributions) in one or more of the following areas: Graph-based machine learning, including predictive, causal or neuro-symbolic models. NLP techniques, including information extraction, text mining, and entity linking. Experience with transformer-based models is a plus. Application of LLMs to defence or similarly complex problem spaces. Graph-structured data, including graph algorithm design and use of relational/graph databases. Knowledge representation and semantic reasoning, including ontology development. Additional Desirable Experience: Hands-on experience with graph ML toolkits (e.g., PyTorch-Geometric, PyKeen) and knowledge graph platforms (e.g., Neo4j). Proficiency in query languages such as SQL or Cypher. Understanding of semantic technologies or LLM-based reasoning systems. Reference: AMC/RHU/RSB ryhu