PhD Studentship in Metamodelling of Speech Domains

Our September 2023 intake (“Cohort 5”) was our final cohort of students. We are no longer recruiting students to join the CDT. 

However, the CDT has funds available to support one affiliated, fully-funded 3.5 year PhD studentship in Spoken Language Technologies. As an affiliated student, you will be welcome to participate in CDT activities and events but you will not be a formal member of the CDT and you will undertake the University of Sheffield’s standard Doctoral Development Programme (DDP) training programme as opposed to the CDT’s PGDip training programme. You will start in September 2026.

Home and International students may apply. Regardless of your fees status (Home or International), all fees will be paid (in addition to a full stipend). International candidates should be aware that the award does not cover funding for costs related to relocation to the UK, such as visa fees or the NHS surcharge. 

This studentship is currently advertised on jobs.ac.uk and FindAPhD.

Affiliated studentship project

We are seeking an excellent candidate to work on a specific speech processing project; the project is supervised by Prof Thomas Hain (a world leader in speech recognition and Fellow of the International Speech Communication Association, ISCA). 

Speech is a highly variable signal that is often recorded in complex environments and under sub-optimal conditions. The information contained in a recorded speech signal is not limited to  just the words spoken; the signal also includes, for example, information on speaker identity or conversation style. Depending on the task at hand, different aspects of the speech signal are important, leading to different models being used. However, in recent years model topologies for automatic speech recognition and many other speech processing tasks have started to converge – driven by research focus on generalisation. Still, the issue of domain dependence often remains. Recently there has been an increased interest in model combination and model editing, for example through disentanglement of so-called task vectors. 

In this project we aim to explore how different aspects of speech data are expressed in model space, in the context of automatic speech recognition and diarisation. The objective of this work is to explore methods to attribute elements of model spaces to skills, or specific aspects of the data. This can be used either as input in hypermodelling, where new models for specific domains are generated, or for improved structuring in model training and design. 

Work on this project  will require research into novel methods to represent model variations and attribute them to specific attributes and tasks. The value of such models should then be demonstrated by informing training and inference processes. A range of different strategies can be explored, including new ways to derive model distributions and model parameter predictions. Experiments should be conducted on a range of tasks of different complexity in the context of different data domains, for example speech classification, speech recognition, and diarisation.

Why apply?

The studentship offers you the following benefits:

• Fully funded 3.5 year studentship covering Home or International tuition fees and an enhanced stipend at the basic UKRI rate plus £3,500 (totalling £25,305 per year, tax free for 2026/27)*.

• Research and training support grant of £2,500 per annum to cover research expenses and conference attendance. 

• Supervision from world-renowned academics.

• Laptop and dedicated desk in the CDT’s student workspace equipped with dual external monitors, keyboard and mouse, and headset.

• Exposure to the cross-disciplinary approaches and co-creation of novel SLT methods and applications.

• A dedicated workspace purely for CDT and affiliated students within a collaborative and inclusive research environment hosted by the School of Computer Science.

• Enrollment on the University of Sheffield’s Doctoral Development Programme (DDP) training programme. 

• Work and live in Sheffield – a cultural centre on the edge of the Peak District National Park which is in the top ten most affordable UK university cities (3rd the Unifresher Cheapest Cities In The UK For Students To Live In 2026; 3rd lowest in the UK for average rent in the NatWest Student Living Index 2025).

How to apply

If you are interested, please apply by 23:59 (UK time) on 19 April 2026.

Short-listed applicants will be invited to interview in Sheffield or via videoconference to be held in mid- to late-May.

Applications received after the deadline will only be considered if the position remains unfilled following these interviews. In this case, we will operate a rolling first-come-first-served process of application review and, where applicable, interview.

You can apply through the University of Sheffield’s Postgraduate Online Application System. *** Please ensure you follow our Application Instructions which will guide you through the application process. ***

If you have any questions about applying please take a look at our FAQ. If you can’t find an answer to your question there, please email us at sltcdt-enquiries@sheffield.ac.uk

Please note we will retain your email address for the purpose of communicating with you about applying to study at the CDT only. Your contact details will not be used for any other topic, nor passed on to anybody else.

Entry requirements

You should have, or be expecting to obtain, a high-quality undergraduate (ideally first class) or masters (ideally distinction) degree in a relevant discipline. 

Suitable backgrounds are (but not limited to):

• Computer Science

• Engineering (e.g., electrical and electronic engineering, control engineering, etc.)

• Mathematics

Regardless of background, you must be able to demonstrate strong mathematical aptitude (minimally to UK A-Level standard or equivalent) and good experience of programming.

We will also consider applicants with a professional background, so long as you are able to provide evidence of demonstrable academic skills as well as practical experience.

We particularly encourage applications from members of groups that are underrepresented in technology.

If English is not your first language, you will need to meet our English Language Requirements. You must have an IELTS grade of 6.5 overall with a minimum of 6.0 in each component.

Equivalent scores in other English language qualifications are welcome; see the University’s guidance for more information on permitted qualifications.

Home and International Eligibility

All students (regardless of Home or International fees status) are eligible to apply and, if successful, will receive the full stipend and all fees are paid. 

To be classed as a home student, you must meet one of the following criteria:

• Be a UK National (meeting residency requirements)

• Be an Irish national (meeting residency requirements)

• Have settled status

• Have pre-settled status (meeting residency requirements)

• Have indefinite leave to remain or enter

If you do not meet the criteria above for Home eligibility, you will be classed as an international student. For full eligibility details, please refer to the UKRI Training Grant Guidance (p24).

When applying, please indicate in your personal statement whether the criteria above classify you as a home student or an international student.