Publisher
source

University of Sheffield

PhD in Reliable and Efficient Adaptation of Large Language Models University of Sheffield in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD studentship covering the standard UK tuition fee and a tax-free stipend at the standard UKRI rate (currently £21,805 for the 2026/27 academic year) for 3.5 years, plus a research training support grant for training, travel, and conference attendance. Overseas students may apply but must secure additional funding or self-fund the difference between UK and overseas tuition fees.

Deadline

Expired

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Country

United Kingdom

University

University of Sheffield

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Keywords

Computer Science
Machine Learning
Information Technology
Mathematics
Natural Language Processing
Interpretability
Large Language Models

About this position

PhD opportunity in Reliable and Efficient Adaptation of Large Language Models at the University of Sheffield, School of Computer Science, with supervision by Dr Cass Zhixue Zhao and Prof Nikos Aletras.

This project focuses on large language models, post-training adaptation, model editing, fine-tuning, activation steering, mechanistic interpretability, and trustworthy AI. The aim is to develop methods that make LLM adaptation more reliable, explainable, efficient, persistent, and safe, while preserving reasoning, fairness, and safety under limited compute.

Possible research directions include detecting intended and unintended changes in internal representations, designing lightweight monitoring methods, and building evaluation frameworks and open-source tools for safe adaptation. The project is well suited to students interested in Computer Science, Machine Learning, Natural Language Processing, and related mathematical methods.

Funding: This is a funded PhD studentship. It covers the standard UK tuition fee and provides a tax-free stipend at the standard UKRI rate (currently £21,805 for 2026/27) for 3.5 years, plus a research training support grant. Overseas applicants may apply, but must cover the difference between UK and overseas tuition fees through additional funding or self-funding.

Eligibility: Applicants should have or expect a degree equivalent to a UK 2:1 in Computer Science, AI, mathematics, or a related field. Strong ML/NLP foundations, Python and PyTorch experience, familiarity with language models/Transformers/generative AI, and an interest in trustworthy, explainable, or efficient AI are preferred. Prior publications are welcome but not required.

How to apply: Submit your application through the University of Sheffield postgraduate online application form. Include a research proposal of up to 4 A4 pages with references, a CV, academic transcripts, a brief research statement, and two referees. Be sure to name Dr Cass Zhao and Prof Nikos Aletras as your proposed supervisors.

Deadline: 2026-08-23.

Funding details

Funded PhD studentship covering the standard UK tuition fee and a tax-free stipend at the standard UKRI rate (currently £21,805 for the 2026/27 academic year) for 3.5 years, plus a research training support grant for training, travel, and conference attendance. Overseas students may apply but must secure additional funding or self-fund the difference between UK and overseas tuition fees.

What's required

Applicants should have or expect to obtain an undergraduate degree at least equivalent to a UK 2:1 honours degree in Computer Science, AI, mathematics, or a related discipline. Strong foundation in machine learning or NLP, Python proficiency, PyTorch experience, familiarity with language models, Transformers, or generative AI, ability to conduct independent research, and interest in trustworthy, explainable, or efficient AI are required or strongly preferred. Prior publications are welcome but not required, and applicants from adjacent fields with strong mathematical or ML experience are encouraged to apply.

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