"Postdoctoral Research Associate"

About us

We are seeking to appoint a postdoctoral research associate with an excellent track record in semantic technologies and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge engineering, linked data, web technologies.

About the role

The successful candidate will join the Distributed AI (DAI) group in the Department of Informatics, King’s College London. They will carry out research in neuro-symbolic AI, with a focus on using generative and agentic AI, as well as AI standards to create trustworthy information resources. This includes the design of algorithms, tools, and process for knowledge workers to better organise knowledge bases and maintain the integrity of their information.

The post holder will work closely with Prof Elena Simperl and a team of 15+ researchers and PhD students in the area of human-centric AI. The role covers research in the areas mentioned above, as well as the production of scientific publications and application showcases to drive research impact. The researcher will be expected to support impact creation activities, including hackathons, workshops, tutorials and to actively contribute to ongoing AI standardisation efforts such as MLCommons Croissant. The research and innovation outputs will inform work undertaken in the group in several large collaborative grants and application areas, including arts and culture, enterprise data management, legal compliance.

The ideal candidate will have solid expertise in the technical areas mentioned earlier, as well as a proven track record of scientific excellence (through publications in A and A* conferences and journals) and of open science and FAIR practices (through software, datasets and other research outputs, participation in challenges etc). Familiarity with semantic technologies and neuro-symbolic AI, in theory and practice, is a firm requirement.

The post is full-time, but we can discuss part-time options in exceptional circumstances. There is also the option to extend the contract beyond the 18 months provided funding is available.

About you

Essential criteria

1. PhD in computer science, AI or related area
2. Proven experience of semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS, OWL
3. Proven experience with predictive and generative AI
4. Practical experience in using large language models, generative AI techniques, prompt engineering
5. Proven record of A/A* scientific publications and open science/FAIR practices
6. Teamwork skills demonstrated e.g. through project work, organisation of joint events, co-authored papers etc.
7. Time management and organisational skills, including experience in organizing small scientific workshops and similar

Desirable criteria

1. Familiarity with the design of AI enabled tools, AI assistants, and agentic AI
2. Familiarity and contributions to Wikipedia and/or Wikidata
3. Understanding and practical experience with FAIR and open science practices
4. Familiarity and contributions to AI or web standards
5. Experience in scientific communication for non-academic audiences
6. Familiarity with one or more of these application domains for neuro-symbolic AI: law, arts and culture, enterprise data management
7. Track record of organising dissemination and community building events e.g. workshops or tutorials co-located with academic conferences

Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.

Grade and Salary: £44,105 to £51,485 per annum inclusive of London Weighting

Job ID: 135825

Post Date: 16-Jan-2026

Close Date: 20-Feb-2026

Contact Person: Elena Simperl

Contact Details: Elena.simperl@kcl.ac.uk