Local Large Language Models to Enable Discovery and Access
A postdoctoral fellowship for early career researchers, as part of the Joanna and Graham Barker Fellowship Scheme.
A postdoctoral fellowship for early career researchers, as part of the Joanna and Graham Barker Fellowship Scheme.
Co-design a research project with the Library exploring how large language models can be used in personal digital archives, where you will be embedded in our expert curatorial and research teams. Applications are now open on our recruitment portal and will close on 15 July 2026.
Open to postdoctoral, early-career researchers who hold a doctorate in a relevant subject or have equivalent experience. The Fellowship will begin on 1 September 2026 and can be undertaken over 12-months full time, or longer part time. Fellows will be contracted for the duration of the fellowship, receiving a salary of £35,993 per annum and employee benefits.
Personal Digital Archives (PDAs) are collections of born-digital materials created over a person’s life and work. These include e-mails, documents, photographs, system files, voice recordings and other digital content. The Library’s collection is the largest and most significant in the UK, and we play a leading international role in developing their preservation, description, and access.
Despite their value, PDAs present major challenges due to their scale and sensitive content and as a result many of these collections remain inaccessible to the public. You will explore how ‘local’ (offline) Large Language Models (LLMs) can be applied to PDAs, developing a case study approach to demonstrate how these tools can improve access and interpretation.
We have a range of archives of notable figures you may wish to work with, including:
This project will be supervised by Callum McKean, Lead Curator for Born-Digital Archives.
Download the full project outline (PDF, 150.8KB).
Thanks to a generous donation from Joanna and Graham Barker, this early career fellowship scheme is designed to support and equip researchers, creatives and cultural professionals with the practical skills, professional insight and interdisciplinary experience needed to thrive in a rapidly changing knowledge landscape. A key element of this opportunity is to provide a structured pathway for Fellows to gain transferable, future-facing skills, project- and line-management experience, feel supported within our research community, and generate new expertise for the wider world.
Fellows will be hosted and supervised within the relevant area of the Library and supported by the Research Development team. They will be embedded within their team, provided with desk space and ICT equipment and will benefit from privileged staff-level access to collections.
The Fellow will also be invited to join departmental meetings enabling them to learn more about curatorial activities and the wider collections. They will be offered mentorship, networking, and assisted in identifying opportunities to gain experience in institutional research culture, public programming, and collections-based scholarship. They will be able to access the wide range of workshops, talks, training and expertise available at the Library, including but not limited to: the Digital Scholarship Training Programme, Cultural Property Training, Researcher Packed Lunches and Carbon Literacy training.
By the conclusion of the Fellowship, each Fellow will have:
To apply for a fellowship, you must meet all the following criteria:
If you have passed your viva before the application deadline with minor corrections, you are eligible to apply. You will not be eligible if you must make major corrections which need to be re-assessed so the final submission of your thesis falls after the application deadline.
Submit your application on our recruitment panel.
To apply, please:
The assessment panel will consider the following criteria:
Once selected, the Fellow will further refine the research topic and incorporated PhD Placement alongside the Library Supervisor and Research Development team, in order to gain maximum benefit from the collaboration.