The University of Manchester invites applications for a post-doctoral Research Associate in AI and text analytics to work on an AHRC-funded multi-disciplinary research project "Our Heritage, Our Stories: Linking and searching community-generated digital content to develop the people's national collection". The project, part of the Towards a National Collection: Opening UK Heritage to the World (TaNC) programme, will develop cutting-edge approaches for scalable search, linking and discoverability across community-generated digital content (CGDC) and the national collections of The National Archives (TNA).
The successful candidate will focus on developing natural language processing-based methods for automated extraction and semantic enrichment of CGDC metadata from disparate collection descriptions, and will build associated knowledge graphs to enable complex representations and search. This is an excellent opportunity for an experienced and enthusiastic researcher to join a multi-disciplinary team to work with real-world community data and demonstrate the potential of AI in making previously unfindable and unlinkable CGDC, discoverable within the national collection, while respecting and embracing its complexity and diversity. Based in the Department of Computer Science at Manchester, the post will be closely linked to the Emerging Technologies Research team at TNA and researchers in digital humanities, archives, history and linguistics at the Universities of Manchester and Glasgow, and will collaborate with leading UK heritage organisations, including Tate, the British Museum, the National Libraries of Scotland and Wales, the National Lottery Heritage Fund, the Public Record Office of Northern Ireland, and a network of smaller regional and local heritage organisations holding digital content created by and relating to communities. Further details can be found at https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=23281 How to apply: Applications are to be submitted online at https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=23281 Deadline for applications: 27 September 2022
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