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Postdoctoral Research Associate

King's College London

London

On-site

GBP 35,000 - 45,000

Full time

6 days ago
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Job summary

A leading education institution is seeking a postdoctoral research fellow in the Department of Informatics. The role focuses on neuro-symbolic AI, utilizing generative AI for knowledge graph engineering, engaging with a research team to drive impact in various application domains. Candidates should hold a PhD in a relevant field and possess expertise in AI technologies.

Qualifications

  • Proven experience in knowledge graphs and data modeling.
  • Experience with large language models and generative AI techniques.
  • Record of publications in A and A* conferences.

Responsibilities

  • Conduct research in neuro-symbolic AI focusing on generative AI.
  • Design algorithms and architectures for knowledge graphs.
  • Produce scientific publications and support community engagement activities.

Skills

Knowledge engineering
Semantic technologies
Predictive AI
Generative AI
Prompt engineering
Teamwork skills
Time management

Education

PhD in computer science, AI or related area

Job description

About us

The Department of Informatics is seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, 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, 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 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 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 and application showcases to drive research impact. The researcher will also be expected to support the organisation of impact creation activities, including hackathons, workshops, tutorials, and 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 and 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 and experience:

Essential criteria

1. PhD in computer science, AI or related area

2. Proven experience of knowledge engineering and 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, organization 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. Familiarity with one or more of these application domains for neuro-symbolic AI: law, cultural heritage, enterprise data management

4. 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 Now". This document will provide information of what criteria will be assessed at each stage of the recruitment process.

* 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.

Further Information

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.

We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

To find out how our managers will review your application, please take a look at our ' How we Recruit ' pages.
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