Postdoctoral Researcher in Large Language Model Development
University of Oxford – Humanities Divisional Office · United Kingdom
Postdoctoral researcher position at University of Oxford to develop large language models for humanities research. Role involves curating multilingual training data, pre-training and fine-tuning foundation models, designing evaluation benchmarks, and publishing open-source resources. Requires PhD/DPhil or substantial machine learning experience and ability to engage with historical texts.
This opportunity has closed.
About this opportunity
Contract
Fixed term for 12 months
Hours
Full-time (37.5 per week)
About the role
The postholder is expected primarily to deliver the core objectives of the BodleianLLM project: curating, cleaning and documenting a multilingual humanities training corpus drawn from Oxford's GLAM collections; performing continual pre-training and fine-tuning of an open-weight foundation model on the University's own computing infrastructure; and, working with subject specialists and curators, designing and validating the first dedicated benchmark suite for evaluating language models on humanities research tasks.
You will also be expected to publish the model weights, code, corpus documentation and benchmarks as fully open-source resources; to contribute to the technical roadmap for a major follow-on funding bid; to collaborate on research publications and present at conferences; and to help deliver the project's one-day workshop for the GLAM, digital humanities and AI communities. You will report to the Principal Investigator, Professor Glenn Roe, with day-to-day technical supervision from a Senior Research Software Engineer at Digital Scholarship at Oxford (DiSc).
About you
You will hold a relevant PhD/DPhil or have substantial experience of machine learning in a research or industry environment, and have the ability and willingness to combine machine learning research with sustained engagement with historical and multilingual source material. You will have a strong understanding of deep learning and natural language processing, with practical experience of training, adapting and deploying large language models.
You will also be able to process and transform historical, multilingual or otherwise non-standard textual data and to design and validate evaluation benchmarks; have strong Python and software engineering skills; have a strong publication record commensurate with experience; and have excellent communication and organisational skills. Experience of cultural heritage collections, reading knowledge of historical languages, and familiarity with HPC and MLOps practice would be desirable.
The duties and skills required are described in further detail in the job description.
Application process
Applications for this vacancy are to be made online.
For your online application, you will be required to upload your curriculum vitae and a supporting statement. The supporting statement must demonstrate that you meet each of the selection criteria for the post, using examples of your skills and experience. This may include experience gained in employment, education, or during career breaks (such as time out to care for dependents).
As part of your application you will be asked to provide details of two referees and indicate whether we can contact them now. References will only be requested for shortlisted candidates.
For further details, please refer to the How to apply section of the job description. Any further enquires about the application process may be directed to hr@humanities.ox.ac.uk.
The closing date for applications is 12.00 noon on 12 October 2026. Only applications received before this time can be considered.
Please quote Vacancy ID 188861 on all correspondence.
We welcome applications from a broad and diverse range of applicants: if you have any access needs or requirements to make your application journey more accessible, please let us know and we will do our best to facilitate.
Committed to equality and valuing diversity.
Eligibility
Not specified by the source
Academic requirements
You will hold a relevant PhD/DPhil or have substantial experience of machine learning in a research or industry environment, and have the ability and willingness to combine machine learning research with sustained engagement with historical and multilingual source material.
English language requirements
Not specified by the source
How to apply
Not specified by the source