Postdoctoral Research Associate - Prompt Engineering as Knowledge Engineering

    We are seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs and 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.

    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 and architectures, but also process blueprints and 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 10 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 and application showcases to drive research impact. The researcher will also be expected to support the organisation of research hackathons in prompt engineering for knowledge engineering, aligned with the activities of the Knowledge Graph Interest Group at the Alan Turing Institute. 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* journals) and of open science and FAIR practices (through software, datasets and other research outputs, participation in challenges etc). Familiarity with ontology engineering methodologies, in theory and practice, is a bonus, but not 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 12 months provided funding is available.

    This post will be offered on an fixed-term contract for 12 months

    This is a full-time post - 100% full time equivalent

    Key responsibilities

    Lead the development of methods, software and datasets that fulfil the goals and requirements as specified in the project
    Communicate the scientific achievements in scientific papers, engaging in advanced research
    Develop research showcases to increase research impact
    Co-organise and support research hackathons on the topic of the project
    Undertake any other reasonable duties that may be requested by the co-investigator
    The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

    Skills, knowledge, and experience

    Essential criteria

    Knowledge graphs
    Machine learning
    Large language models
    Generative AI
    Proven record of A/A* scientific publications and open science/FAIR practices
    Teamwork skills
    Time management and organizational skills (including experience in organizing small scientific workshops and similar)
    Desirable criteria

    At least one of the following: natural language processing, large language models, graph learning, general pre-trained transformers, knowledge representation, knowledge engineering methodologies, prompt engineering

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