About this role
About us
We are seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, semantic technologies, & machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, general pre-trained transformers, prompt engineering, knowledge graphs, knowledge representation, knowledge engineering, linked data.
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 AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms & architectures, but also process blueprints & guidance for knowledge engineers to use generative AI tools productively.
The post holder will work closely with Prof Elena Simperl and Dr Albert Meroño Peñuela and a team of 15+ researchers and PhD students in the area of knowledge graphs. The role covers research in the areas mentioned above, as well as the production of scientific publications & application showcases to drive research impact. The researcher will also be expected to support the organisation of impact creation activities, including hackathons, workshops, tutorials, & community meetups. The research outputs will inform work undertaken in the group in several large collaborative grants and application areas, including cultural heritage, enterprise data management, and 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 & other research outputs, participation in challenges etc). Familiarity with knowledge engineering methodologies and with semantic technologies, in theory and practice, is a firm requirement.
The post is full-time (35 hours per week) offered on a fixed-term contract for 18 months. 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
To be successful in this role, we are looking for candidates to have the following skills & experience:
Essential criteria
PhD in computer science, AI or related area Proven experience of semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS, OWL Proven experience with predictive & generative AI Practical experience in using large language models, generative AI techniques, prompt engineering Proven record of A/A* scientific publications and open science/FAIR practices Teamwork skills demonstrated e.g. through project work, organisation of joint events, co-authored papers etc. Time management and organisational skills, including experience in organizing small scientific workshops & similar
Desirable criteria
Familiarity with the design of AI enabled tools, AI assistants, and agentic AI Familiarity and contributions to Wikipedia and/or Wikidata Understanding and practical experience with FAIR and open science practices Familiarity and contributions to AI or web standards Experience in scientific communication for non-academic audiences Familiarity with one or more of these application domains for neuro-symbolic AI: law, arts and culture, enterprise data management Track record of organising dissemination and community building events e.g. workshops or tutorials co-located with academic conferences
Downloading a copy of our Job Description
Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply”.