Apply for affiliated studentships

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 two affiliated, fully-funded 3.5 year PhD studentships 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 2025.

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. 

Projects available

We are seeking two candidates to each work on a specific project in Spoken Language Technologies research. These projects specifically target interdisciplinary research, covering both fields of speech and language research. 

The projects are jointly supervised by Prof Thomas Hain (a world leader in speech recognition and Fellow of the International Speech Communication Association, ISCA) and Prof Rob Gaizauskas (internationally known for his research on information extraction and text mining, temporal information processing, question answering and summarisation). 

You will be working on one of the following topics:

Project 1: Accessible Democracy

UK Houses of Parliament and cross-party Select Committees are at the core of our democracy. Making the proceedings of these bodies accessible to citizens and journalists is key to holding politicians accountable. This research aims to develop technologies to provide access to the rich linguistic and paralinguistic information in parliamentary audio recordings. Helping journalists to identify newsworthy events is one of the example objectives, alongside more standard tasks such as search, creating alerts or summarisation.

Project 2: Analytics of conversations

Spoken conversations are complex and difficult to understand for AI systems. While the words spoken are of obvious importance, paralinguistic information often plays an essential role for a satisfactory and efficient exchange. In practice only goal oriented metrics are used to assess the quality of an exchange, which are not helpful to describe a wide range of conversations such as interviews, story telling or even examinations. Modelling of the participants’ knowledge and state as well as paralinguistic signalling and perception should be used to research novel methods to interpret and understand conversations. 

Project 3: Evolving communication in embodied agents

Spoken and written language have developed in the course of human evolution and can be viewed as key species-wide adaptations that have enabled us to better survive on our planet. Modelling the development of language in artificial agents with sensory apparatus that are embedded in a physical environment is an exciting research methodology that promises both deeper understanding of human languages and their origins,  as well as insights into how to build more effective autonomous agents. This research will build on the state of the art in this area. 

Why apply?

The studentship offers you the following benefits:

How to apply

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):

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.

How to apply

If you are interested, please apply by 23:59 on 13 April 2025. Applications will then be reviewed and short-listed applicants will be invited to interview. Interviews will be held in Sheffield or via videoconference in mid- to late-May.

Applications received after the deadline will only be considered if either 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.

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:

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.

* Tax and National Insurance: Stipend payments are training awards and not regarded as income for income tax purposes. Earnings received from sources such as teaching and demonstrating may be taxable and should be aggregated with income from any employment when assessing income tax liability in any tax year – this is particularly relevant for the tax year in which the award ends. It is your responsibility to ensure you understand your tax liabilities throughout your award. The University and UKRI are not able to provide advice on tax, national insurance, pensions or on benefits issues.

No additional payments will be made for your National Insurance contributions. You can, if you wish, pay contributions as non-employed persons. You should consult your local office of the Department for Work and Pensions about your position to determine the impact of non-payment of contributions on any future claims for benefit including the basic State Pension. You may become liable for contributions in connection with any paid teaching or demonstrating which you undertake.