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Stages 1 and 2: Online application forms

To apply for a PhD studentship in the CDT in AI for Digital Media Inclusion, first submit the following online forms, which will be available when recruitment opens in December:

2. .

Send the following to CDT_AI@surrey.ac.uk:

1. Copy of your CV (2 pages max.)
2. Research proposal (800 words max.) (please label your files clearly with your LASTNAME.Name).

Stage 3: Recruitment workshop

Shortlisted candidates will be invited to a recruitment workshop at the �ۿ۴�ý (there will be an online option for those who need to attend remotely).

  The recruitment workshop will include:

• Introduction to the CDT in AI for Digital Media Inclusion and the challenge-led research training programme with industry.
• Group task working in small multi-disciplinary groups to propose an approach using AI to enable inclusion for all in a media experience.
• Interview with a panel to further explore motivation, passion for the subject, ability to engage in interdisciplinary thinking and problem-solving skills. This will include a discussion of the research proposal submitted.

Outcomes and decisions:  Pre-selection stage

Applicants will be notified by email when a decision has been made. For applicants accepted onto the CDT programme, a provisional offer will be made by the CDT subject to completion and submission of a formal PhD application via the chosen University (�ۿ۴�ý or Royal Holloway University of London) portals with the required documentation.

The deadline by which applicants must accept their CDT provisional offer will be stated in the notification email. Candidates will be invited to discuss their preferred location for their PhD studies (�ۿ۴�ý/Royal Holloway University of London) prior to the formal offer being issued.

Stage 4: University official PhD offers

Formal offers (academic and funding) will be made by either the University in line with the academic and language requirements set out in the admissions statement for the programme, taking into account relevant experience.

Offers may be conditional or unconditional:

• Unconditional offers will be made where applicants have already met the conditions and provided evidence.
• Conditional offers will be made where academic or language qualifications have not yet been fulfilled, specifying the requirements that must be met. 

CDT candidates additional information (online form two)

The CDT candidates additional information (form two) contains standardised monitoring questions about your personal characteristics. You are not obliged to provide this information and it will not form part of the assessment process. We will use it to evaluate our equality, diversity and inclusion practices and report back to our funder. All questions include the option 'prefer not to say'.

As the CDT is publicly funded by UKRI, we are required to collect information about applicants seeking to be considered for this PhD programme. The data will be treated as confidential and will be held separately from the identifying information that you provide in the first section below.

Only a limited number of CDT members will be able to link the two sets of data. We need to maintain this link so that we can understand applicants’ interactions with us over time without asking you to provide the information multiple times.

Case study guidelines

You are required to submit a case study (600 words max.) that reflects a specific idea or example in which AI could be applied to improve digital media inclusion. Your case does not need to be researched in detail. Please focus on identifying a single, innovative idea and communicating it clearly.

Your case study and a copy of your CV (2 pages max) need to be submitted by the same deadline as the online form: UK or UK-resident applicants: 2 May 2025*. Overseas quota now full.

*We reserve the right to close applications earlier if we reach our target.

Case study task structure

• Title: A brief title that communicates the essence of the idea
• Overview (max 200 words): A top-level description of a specific way in which AI could be applied to improve digital media inclusion
• Inclusion impact (max 200 words): A more detailed explanation of the potential of this innovation for improving inclusion
• Challenges (max 200 words): A critical evaluation of the potential challenges involved in delivering this vision both technical and non-technical.

Case study scoring

Case studies will form part of the pre-selection process and will be discussed with you on the selection day. They will be scored based on the following criteria:

• Fit to ‘AI for digital media inclusion’ brief
• Clarity of communication
• Critical evaluation.

Your case study score will be combined with other scores of the selection day criteria to inform the final decision.

The selection process will be conducted by members of staff who have been trained in equality, diversity and inclusion with respect to recruitment techniques. All interviews and selection processes will be undertaken in accordance with the University’s policy on equal opportunities.

All applicants are considered in line with the University’s relevant code of practice for postgraduate admissions.

Your completed online application (form one), CV and case study will be used to assess your initial eligibility and suitability for the programme. We’re looking for academic excellence, passion for research on AI for digital media inclusion, and evidence of being able to work in a team.

Applications are considered by at least two members of staff using the following criteria:

• Academic achievement and relevant experience (50%)
• Motivation and case study (30%)
• Fit to multi-disciplinary cohort and teamwork (20%).

Our scholarships funding is provided for a period of four years and covers:

• UK home tuition fees
• Tax-free maintenance payment based on the UK Research and Innovation (UKRI) minimum rate: UKRI recently announced a stipend increase for 2025/2026 to be £20,780 per year from 1st October 2025
• Enhanced supplement of £4,000 per year
• The conditions of the scholarship are that you work no more than 20 hours per week outside of your funded PhD research
• As a doctoral student, you may be able to access additional funding to cover the cost of other related training and development opportunities.

Prospective candidates can contact CDT_AI@surrey.ac.uk for more details.

You can also contact members of the team for academic guidance:

• Professor Adrian Hilton – CDT Director: a.hilton@surrey.ac.uk
• Professor Polly Dalton – CDT Co-Director: polly.dalton@rhul.ac.uk
• Jonathan Winfield - CDT Manager: jonathan.winfield@surrey.ac.uk.