Funding opportunity

Funding opportunity: UKRI Centres for Doctoral Training in artificial intelligence

Apply for funding for a Centre for Doctoral Training (CDT) focused on the applications and implications of artificial intelligence (AI).

You must be based at a UK research organisation eligible for UK Research and Innovation (UKRI) funding.

Proposals are welcomed within priority areas across the remit of UKRI addressing UK training needs in novel and existing AI technologies.

CDTs will deliver high quality, cohort-based doctoral education.

Up to £117 million is available to support 10 to 15 CDTs. UKRI will fund 100% of the full economic cost.

CDTs will train 5 cohorts of students doing a 4-year doctorate or equivalent. The first cohort will start in the 2024 to 2025 academic year.

UKRI held a webinar to support this funding opportunity on 13 January 2023. The materials from this webinar are available in the ‘Additional information’ section.

Who can apply

Organisational eligibility

Applications are invited from eligible organisations or consortia that can demonstrate the ability to host a Centre for Doctoral Training (CDT) in areas of AI. Centres should address UK skills needs in AI at the doctoral level through the provision of both breadth and depth of research training.

Check if your institution is eligible for funding.

You should demonstrate the ability to host a CDT by meeting all the criteria detailed. This includes a critical mass of supervisors (around 20 to 40) existing across the partnership of the application and a proven track record of doctoral supervision.

Centres will be expected to support at least 50 students over the duration of the funding period. Smaller numbers may be permitted by exception where they can be fully justified due to the nature of the training. Please contact UKRI in advance of submission should you wish to apply for smaller cohorts.

Applications are welcomed equally from single and multi-organisational teams. Collaborations with non-academic project partners are expected where appropriate for the focus of the centre. In assembling the centre team, applicants must consider what is most beneficial to the centre vision, research environment and training provision being proposed. We welcome CDT proposals which include elements of international engagement where they add value to the proposed centre.

Applications must be led by research organisations which already have suitable arrangements in place to award doctoral qualifications and a track record of delivering doctoral training. Other research organisations eligible for UKRI funding may partner on proposals. Organisations not eligible for research council funding, for example businesses, may be named as project partners.

Individual eligibility

The principal investigator must be from the lead organisation for the application.

As the Engineering and Physical Sciences Research Council (EPSRC) is the council to which proposals are being submitted, you must follow their rules for eligibility.

Check if you’re eligible for funding.

The principal investigator and co-investigators must be from an eligible UK organisation.

We also welcome Professional Research and Investment Strategy Managers (PRISM) who are integral to developing the CDT bid as co-investigators.

New and existing CDTs

Applications to refresh existing UKRI AI CDTs are welcomed as well as applications to support new CDTs. All applications will be considered together. They will be treated equally and assessed using the same assessment process and criteria.

UKRI will not set any expectation on the number of existing or new centres that will be supported. Information about existing centres will not be made available to peer review by UKRI.

Demand management

It is expected that this UKRI AI CDT opportunity will be in high demand. As such organisations may submit a maximum of 2 outline applications to this funding opportunity as lead organisation, that is the organisation submitting the application through the Joint Electronic Submission (Je-S) system. This reflects the level of investment available and manages the impact on the community in assessing the large volume of proposals anticipated.

We strongly encourage collaborative, cross-disciplinary bids across faculties and between organisations. There will be no limit on the number of applications that eligible organisations can partner on.

Only successful outline applications will be invited to submit a full proposal. The success of an outline will be based on performance against the assessment criteria and the balance of proposals across the set of outlines under consideration. The overall number of outlines allowed to proceed will be limited to ensure a robust assessment of full proposals is possible. Organisational quotas will not form part of the decision.

Repeatedly unsuccessful applicants

Submissions to this funding opportunity will not count towards the EPSRC repeatedly unsuccessful applicants policy.

What we're looking for


We are looking to support Centres for Doctoral Training (CDTs) to deliver high quality, cohort-based doctoral training in the applications and implications of novel and existing AI technologies.

It is expected that all those trained through the CDTs should have a sufficient knowledge of AI and the chosen priority area such that at the end of their studies they will be able to develop and apply novel AI techniques within that area, discipline or sector.

CDTs should have an emphasis on a high value student experience promoting their long-term career development, wellbeing, and preparation to follow a diversity of career paths.

Applications are required to demonstrate the specific need for doctoral training through the CDT mechanism which includes the following key features:

  • a clear need for doctoral level skills education in a specific area of focus
  • the need for a cohort-based training approach
  • the provision of both depth and breadth in the research training proposed to address the identified skills need

Co-creation between different disciplines and engagement with industry and users are strongly encouraged. While high-quality proposals in any relevant area of UKRI’s remit are welcome, interdisciplinary proposals are particularly welcome.

Priority areas

CDTs should focus on AI applied and applicable in at least 1 of the priority areas. Centres may focus on more than 1 area. Centres should have a clear vision for the area or areas of AI training they will focus on, be able to articulate the national need for students in that area and explain the benefit of bringing the centre together in a multidisciplinary way.

Proposals must clearly identify which area or areas they will deliver against and the rationale for selection of the areas, including:

  • potential for innovative research training agendas
  • value added synergies
  • evidence of capability to deliver relevant to these areas

The priority areas are outlined below.

Science and research

This priority area covers AI to transform research and discovery across all disciplines, enabling:

  • novel hypotheses to be identified
  • new questions to be explored
  • advanced data-driven approaches to research

You should identify which fields of research the training within the CDT would be relevant to and where synergies may exist with other areas highlighted below, if relevant.


This priority area covers the development and deployment of AI in the understanding and management of health and disease. This includes the prevention, detection, and treatment of diseases through integration of multimodal data and across scales from molecular to populations. Using AI to support health, resilience and wellbeing through life is also within scope. Training may support the use of AI to generate:

  • new cellular, molecular, mechanistic or causal insight
  • understanding of emerging health threats
  • accelerating development of improved health interventions

CDT training is expected to be collaborative and multidisciplinary, open to clinical trainees and other technical specialists. Training should be framed within the responsible delivery of AI in a human health context, and will need to consider complexity, equity, deployment, reproducibility, and fiduciary responsibilities.

Environment and energy

This priority area covers AI to advance our understanding of the natural world and to address critical global environmental and energy challenges. Using AI to harness our rich, complex and diverse environmental data will enable us to understand, predict, evaluate and mitigate the issues of our changing climate. Optimising energy systems with AI and using AI to develop new energy technologies will affect a long-term reduction in carbon emissions.

CDT training will deliver skilled researchers who can tackle interdisciplinary problems such as:

  • weather and climate prediction
  • modelling greenhouse gas emissions
  • optimising use of energy and resources
  • anticipating extreme events due to natural hazards
  • understanding how behaviour change can address environmental challenges
  • understanding uncertainty and risk in environmental models

Owing to the complexity of planetary and energy systems student training should also encompass systems approaches and end-user collaboration.

Sustainable agriculture and food

The agrifood sector must:

  • adapt and build resilience to climate change
  • decarbonise to reach net zero targets
  • reverse biodiversity decline
  • improve animal welfare
  • combat disease threats

The sector must do this while also ensuring a sustainable supply of safe food and delivering positive nutritional, economic and environmental outcomes globally. CDT training will develop students with interdisciplinary AI expertise, including the ability to:

  • harness diverse data to deepen our understanding of soils, crops, aquaculture, farmed animals, supply chains, and consumer demand
  • generate novel insights across scales from lab to landscape
  • generate solutions relevant to real-world needs from industry, policy and other stakeholders across food systems from farm to fork
Defence and security

AI is specifically cited in the UK government’s Integrated Review as a priority technology for development to ensure the ongoing security and defence of the UK.

Applications of AI which can augment better human decision-making at pace, better population responses to threats, automatically detect system vulnerabilities and self-patch software or enhance operational efficiency at scale have the potential to completely change defence and security.

CDTs will deliver students with expertise in the design and use of AI technologies in the defence and security sectors. This includes how AI systems will be used and affect decision making, and the ability to implement solutions ethically and responsibly. You should show how graduates will get the experience necessary to develop AI within the defence and security sectors.

Creative industries

The use and influence of AI in the creative industries is growing, impacting on the development of an increasing range of subsectors. This spans content creation, content consumption and analysis of creative outputs. The spread of AI is further accelerating through digital convergence between sectors, for example, the application of game development techniques in filmmaking.

CDT training will develop researchers with interdisciplinary skills for careers in the creative sector. Students will also develop deep understanding of significant ethical implications and questions of consumer trust, as well as regulatory and legal issues related to the use of AI in these contexts.

Responsible and trustworthy AI

The expanding capabilities and range of applications of AI necessitate new research into responsible approaches to AI that are secure, safe, reliable and that operate in a way we understand, trust, and can investigate if they fail. Ensuring the safe and ethical adoption of AI technologies is vital to ensure that they deliver societal and economic benefits.

CDT training in this area will equip students with interdisciplinary expertise in the development and deployment of responsible and trustworthy AI technologies, including technical knowledge and sociotechnical aspects such as fairness, bias and ethics.

This is a research-focused priority area.

All CDTs will be expected to provide relevant training in responsible research and innovation relating to AI.

Cross-cutting themes

In addition to the above priority areas applicants are encouraged to consider the following cross-cutting themes where appropriate. Applications involving cross-cutting themes should identify clear links with one or more of the priority areas, which sector or sectors the CDT will target, key industry or government partners, and the reciprocal benefits the partnerships will deliver.

AI for increasing business productivity

This theme addresses industry-oriented AI challenges, unlocking the potential of AI to boost innovation, competitiveness and economic activity. The capabilities of AI technology are mature enough for the economy to realise productivity gains, with adoption of AI being the last hurdle to make sure everyone benefits.

CDT training in this theme will ensure the UK has a new generation of researchers equipped with the skills needed by industry to facilitate responsible adoption and exploitation of AI.

Application of AI to government policy and public services

AI technologies have great potential to improve the effectiveness and efficiency of services to the public. By harnessing a range of data assets, it can also better enable data usage to inform policy and to prioritise what works, and for whom.

CDT training should result in students with an understanding of policy development and public services, who are also able to use AI techniques in this context, and who are familiar with datasets and challenges in their usage relevant to policymaking.

Responsible AI

Investing in CDTs in AI will train people across a spectrum, including:

  • those with a background in AI wishing to apply their skills to a wide range of disciplines and challenges
  • those who are from different disciplinary backgrounds, where AI could make a transformational contribution to that discipline or where that discipline could be brought to bear on the development of AI technology and approaches

CDTs should also consider the implications of AI into the intended domains, examining the legal, ethical and socio-economic consequences of potentially disruptive intelligent technologies before they are deployed.

Foundational AI

Proposals focused on the mathematical and computational foundations of AI without a clear application to one of the priority areas should be submitted to the Engineering and Physical Sciences Research Council (EPSRC) CDT funding opportunity. Applicants who are unclear about which funding opportunity is best suited to the vision for their CDT should seek advice from UKRI.

UKRI reserves the right to move applications from this funding opportunity to the EPSRC CDT funding opportunity after the outline assessment, and vice versa, should an application better fit the scope of the other funding opportunity. Applicants who are unclear about which funding opportunity is best suited to the vision for their CDT should seek advice from UKRI.

Key features of CDTs

It is expected that the minimum cohort size will be 10, though exceptions may be made where they can be fully justified due to the nature of the training.

The doctoral education delivered by the CDTs should provide:

  • the support for student cohorts on a 4-year doctorate or equivalent, with a critical mass of supervisors (around 20 to 40) of internationally recognised research excellence and having a track record of doctoral supervision
  • a cohort approach to training through peer-to-peer learning both within and across cohorts. This cohort approach to training should be provided throughout the lifetime of student’s doctorate training programme
  • opportunities for significant, challenging and original research projects leading to the award of a doctoral level degree in accordance with a university’s standard regulations
  • doctoral projects that are designed in such a way that (barring exceptional circumstances) students are able to submit their thesis within their funded period
  • a formal, assessable programme of taught coursework, which should develop and enhance, for example, technical interdisciplinary knowledge such as software and data skills. Courses should also prepare students for future careers, providing trainings in areas such as management, entrepreneurship, commercialisation, responsible innovation and environmental sustainability
  • a significant commitment to and support for the training environment by the hosts and key partners including appropriate co-creation of the centre
  • opportunities for all students to gain experience beyond their doctoral projects
  • appropriate user and employer engagement in the research and training
  • a diverse and inclusive research environment to support people in achieving world-class research and career development
  • mechanisms by which students funded through other routes can benefit from the training experience offered by the centre, and for the centre to reach out to the broader research and user community

You should also consider the aspects listed in the enhanced training section below.


The design and management of CDTs should aim to support the graduation of students with research doctoral level qualifications. Centres can offer all students a PhD or professional doctoral award, for example EngD as appropriate to the individual student, the research project, and the benefit to their future career. Universities are free to choose the type of research doctoral qualification that is offered to students.

Centres may choose to offer all students the same type of qualification or a mixture. Some qualifications have their own requirements so centres must ensure that students are able to meet these criteria if these are to be offered. Centre bids will be assessed against the appropriateness of the training provision offered, not the choice of qualifications to be awarded.

Enhanced training

Responsible innovation

Students must receive training in responsible innovation taking into account the wider implications of research and innovation.

Find out more about responsible innovation.

Students should gain an appreciation of social responsibility, the consideration of ethics and inclusive user engagement as part of designing and conducting research. We would expect students to receive training in the general topic of responsible innovation as well as in issues more specific to the scientific areas relevant to the centre and their project.

Impact and translation

CDTs will support students to maximise the impact of the research they undertake, by providing them with an understanding of how research projects can be designed to include considerations of impact from the start.

Depending on the nature of the CDT, impact training may cover knowledge exchange and maximising academic, environmental, societal and economic impacts from research.

Students should understand the research and innovation lifecycle in which they are participating, including translation of research and consideration of end-use. Where appropriate, training should develop people who are able to work with and across industry sectors, and who can foster new innovative approaches.

In some areas, training could provide understanding of intellectual property, entrepreneurship and commercialisation. Others may require understanding of regulatory and policy considerations.

User engagement

UKRI encourages user engagement across the entirety of its doctoral training. The extent of that engagement varies according to the nature of the research and training and may also vary with the size of the company or user. We encourage all forms of user engagement and contributions where this is beneficial to the training provision. The appropriateness of the support offered will vary depending on both the area, sectors, and type of partner. This should be demonstrated and will be assessed based on the added value of the engagement, not its monetary value.

Wider training experience

Enabling UKRI sponsored research students to benefit from experience outside their home organisation can contribute to the wider training experience possible through a CDT. This can be in the form of, for example:

  • industrial experience
  • entrepreneurial training
  • public engagement activities
  • a period of time spent in an overseas academic collaborator’s laboratory
Facilities and research tools

To carry out AI research, researchers need to be able to access and use a wide range of equipment, facilities and e-infrastructure (software, digital research infrastructure and data).

CDT students will therefore need to be trained in how to use the essential tools for their research. Students should benefit from the environment and accessibility of infrastructure. Access to the necessary infrastructure is good evidence of the suitability of the bidding organisation or organisations as a host for the CDT.

If appropriate to their research, students should also have access to large facilities and national research facilities.

Find an EPSRC facility or resource.

It is not expected that centres create bespoke training courses in the use of essential research tools if access to existing courses is available. Funding for students to attend these courses should be included in applications.

UKRI expects applicants to liaise with the appropriate contacts throughout the development of their application to secure commitment from the facility or trainer. Centres requiring significant interactions with facilities should describe how they will ensure the students receive an excellent grounding in the experimental techniques for their research.

Computational and data-driven research

Students being trained through the UKRI AI CDTs will be using computational and data techniques in their projects, and some may have projects aimed specifically at software development.

It is essential that they are given appropriate training so that they can confidently undertake such research in a manner that represents high professional standards and good practice in software development, data management and ethical use of data. For example, to ensure reproducible research (this may need to include data protection and regulation).

Students should be trained in the principles of open data in accordance with the Concordat on Open Research Data. Centres should ensure research data gathered and generated by students is, wherever possible, made openly available for use by others.

Centres requiring students to undertake computational research should set out a programme of training, tailored to meet the needs of the centre students, and explain how this training will be provided. For students who are required to adapt, extend, or develop software as part of their research we expect them to receive training in relevant programming and software engineering skills, including working collaboratively on code, testing, automation, and revision control.

There is a significant amount of training available and centres should contact potential providers, as they may be able either to provide the training required, or to help with ‘training the trainers’ so that material can be delivered locally and at the most appropriate time.

A list of training courses is provided in the additional information guidance (PDF, 176KB).

Computational research training would be expected to include at least several of the following:

  • fundamentals of computing
  • basic data analysis and curation
  • numerical analysis and algorithm development
  • how to apply computational techniques and data analytics as research tools, in particular the design of experiments and the interpretation of results
  • targeted training in applying and using the standard codes for the particular research area of the CDT
  • matching problems with available and new hardware (desktop, cloud, high performance computing, graphics processing units) and scaling up beyond the desktop

Other research staff

UKRI recognises the importance of research software engineers and support staff in the development and deployment of AI technologies and ensuring that AI is developed in a way which is open and provides broad access to the technology in the public good.

As such, you should consider how you will embed the principle of software sustainability into training and research projects. In addition, you should consider where training packages may be available in the CDT which will support associated and aligned research software engineers, technicians and other support staff, or elsewhere in the academic or user training environment.

Funding available

Up to £117 million is available for this opportunity, subject to approval of a business case. Once indexation is applied to successful awards, we expect to support 10 to 15 CDTs. UKRI will fund 100% of the full economic cost.

Estates and indirect costs will not be funded on these awards.

The duration of award must be 102 months, with a start date between 1 April 2024 to 1 October 2024.

Costs that may be requested from UKRI

It is strongly expected that each centre supports a minimum of 50 students over 5 cohorts. Smaller cohorts may exceptionally be permitted where a strong rationale can be provided.

Studentship costs (fees, stipends and appropriate research training support). It is strongly expected that additional support will be provided from non-UKRI sources to contribute to these costs. UKRI funding may be used flexibly but must support students at a minimum of 50% of their studentship costs. The Research Training Support Grant (RTSG) covers items such as travel and consumables.

Centre delivery, coordination (including between a centre and other parties if justified) and management staff costs can be requested. Costs associated with student supervision may not be included.

Tuition fees and stipend above the minimum rates published by UKRI may be requested.

Get a studentship to fund your doctorate.

However, UKRI will not cover additional college fees. Fees cannot be higher than the fee charged by the university for UK non-research council funded students on similar programmes. Any stipend enhancement should be fully justified in the context of the area of training and UK skills need.

Start up costs should only be included where necessary and should not duplicate existing provision such as where existing centres already have necessary infrastructure in place.

All costs (including stipends and fees) requested in applications should be calculated at current rates with no addition made to consider inflation over the length of the funding period. UKRI will include this indexation at the final funding stage.

Costs should not be included to support students outside the CDT cohorts already supported by funding from other sources. Where a central cost is incurred by the CDT (for example in developing a new training course principally for the CDT students) these ‘aligned’ students may benefit from these.

Additional support or leverage

In recognition of the diversity of potential partners across UKRI’s remit, no minimum leverage requirement has been set for this funding opportunity. However, both cash and in-kind support from non-UKRI sources is strongly expected.

HM Treasury have set an expectation of UKRI achieving significant leverage for this investment, and that universities and their partners will work together to give the best outputs for the UK. As such, all CDTs will be expected to contribute to this to an extent that is appropriate for the scope of the centre. UKRI will work with CDTs to meet leverage expectations over the lifetime of the awards.

Typically, it is expected that leverage of UKRI funds will be achieved through support from the applying organisations or project partners. You may use additional support flexibly to contribute to studentship costs (stipends, fees and RTSG). For example, dedicating full support for some studentships each year, or spreading funding to partially support all the students.

An estimate of the total cash support for each CDT is requested at the outline stage. The purpose is to have a view of the overall cost of a CDT. This financial information will not be seen by the panel but is purely for information for UKRI. Please indicate:

  • funding being requested by the centre from UKRI
  • institutional funding secured
  • additional funding secured from project partners

Studentship costs

Studentship costs consist of 3 elements:

  • stipend
  • fee
  • appropriate RTSG

If you are using the UKRI published rates then you should use the 2022 to 2023 rates without any allowance for inflation over the lifetime of the grant.

For more information on costs, read the additional information guidance (PDF, 176KB).


Equipment over £10,000 in value (including VAT) is not available through this funding opportunity. At the full proposal stage, smaller items of equipment (individually under £10,000) should be included in the ‘directly incurred – other costs’ heading.

Where possible researchers are asked to make use of existing facilities and equipment, including those hosted at other organisations.

Investigators and supervision

The investigators named on the Joint Electronic Submission (Je-S) system application form should represent the core management team of the centre. We would generally expect no more than 10 investigators to be named.

A strong justification will need to be provided for a larger core management team. Any requested funding for investigator time should reflect commitments to centre delivery and should not include individual student supervision related to research projects.

In order to maintain a cohort of this size, it is necessary to have access to a suitable pool of potential supervisors. Experience of current centres demonstrates a need for 20 to 40 supervisors, the majority of whom should have internationally recognised research excellence and a track record of doctoral supervision.

Applications will need to provide evidence of a suitable pool of potential supervisors, taking into account the interdisciplinary focus of the CDT and wider considerations such as equality, diversity and inclusion (EDI). You should not record supervisors on the Je-S application form.

Stakeholder collaboration

Due to the scale of these awards, significant collaboration and leverage (cash or in-kind) will be expected from project partners (for example, business, public sector, third sector). This may include models such as funding studentships, industrial placements, co-created workshops.

We expect collaborations to build a mutually beneficial two-way relationship based on:

  • expertise
  • career development opportunities for students
  • increased depth of understanding of sector by students
  • regional strengths
  • infrastructures

To ensure the awards are inclusive of a variety of approaches and research fields, no specific leverage expectations are being set for this funding opportunity.

Clear plans for engaging with new and existing collaborators over the duration of the CDT should be detailed in the case for support.

Involvement of The Alan Turing Institute

As the UK’s national institute for AI and data science The Alan Turing Institute is well positioned to engage with the UKRI AI CDTs. They will be taking a neutral stance towards all applicants as they intend to work openly and proactively with all successful UKRI AI CDTs. This means they will not be offering specific support to individual centres, for example acting as project partners on any UKRI AI CDT application. They will not offer letters of support to any proposed centres.

Successful CDTs will be brought together after awards are made to discuss opportunities to engage with The Alan Turing Institute but engagement will not be mandated.

Find out more about The Alan Turing Institute.

International involvement

We welcome applications which include elements of international engagement where they add value to the proposed centre. Support requested might include travel, subsistence and consumable costs for UK-based students undertaking training or research visits to overseas centres of excellence, or for leading researchers to visit the UK to contribute to the students’ training experience.

Where a formal, joint training partnership is proposed, the UK component must be able to stand on its own merits. Students registered at international institutions will not count towards the minimum cohorts.

Applicants planning to include international collaborators on their proposal should visit trusted research and innovation for guidance on getting the most out of international collaboration while protecting intellectual property, sensitive research and personal information. Centres will be expected to engage with the relevant regulatory bodies where concerns may arise under the National Security and Investment Act.

Find out more about UKRI’s work around international engagement and partnerships.


The UKRI-RCN Money Follow Cooperation Agreement does not apply to this funding opportunity. As such CDT grants cannot include a Norway-based co-Investigator.

Equality, diversity and inclusion

UKRI aims to support a diverse and inclusive research environment where there is equal access to opportunities.

We are committed to supporting through our investments a diverse range of flexible approaches to ensure we support the diverse needs, backgrounds and potential careers of doctoral students as well as the requirements of the research and innovation communities.

It is therefore a requirement of all UKRI AI CDTs that EDI best practices are embedded into all aspects of the of the doctoral recruitment and training process throughout the lifetime of a training grant including:

  • improved access and diversity of entry points to doctorial education
  • project design, advertisement and applicant support
  • applicant shortlisting and interviews
  • management, training, supervision and tailored student support
  • monitoring and evaluation

Read the EDI expectations guide to help you identify and overcome local barriers and to be used alongside other toolkits provided by organisations and your local institution.

Applications that support job shares, part time contracts and flexible working arrangements for CDT staff, academics and students are welcomed. Part-time students must undertake study for a minimum of 50% full time equivalent.

Cohort engagement

Successful CDTs will be expected to work together as a cohort to share best practice, maximise the value of the investment, and engage with other key actors in the UK AI landscape. This may include subsets of the CDTs where appropriate.

Environmental sustainability

UKRI’s environmental sustainability strategy lays out our ambition to actively lead environmental sustainability across all our investments. CDTs must also seek opportunities to influence others and leave a legacy of environmental sustainability within the broader operations of their academic and industry partners.

How to apply

This funding opportunity will comprise of outline and full proposal stages.

Only 1 Joint Electronic Submission (Je-S) system application will be accepted per Centre for Doctoral Training (CDT) proposal, including for multi-organisation proposals. The Je-S application must be submitted by the lead eligible organisation.

Outline stage

You must apply using the Je-S system.

You can find advice on completing your application in the Je-S handbook.

We recommend you start your application early.

Your host organisation will also be able to provide advice and guidance.

Submitting your application

Before starting an application, you will need to log in or create an account in Je-S.

All investigators involved in the project need to be registered on Je-S.

Any investigators who do not have a Je-S account must register for one at least 7 working days before the opportunity deadline.

When applying:

  1. Select ‘documents’, then ‘new document’.
  2. Select ‘call search’.
  3. To find the opportunity, search for: UKRI Centres for Doctoral Training in Artificial Intelligence.

This will populate:

  • council: EPSRC
  • document type: outline proposal
  • scheme: EPSRC Outline
  • call/type/mode: UKRI Centres for Doctoral Training in Artificial Intelligence

On the Je-S outline application form, you should ensure:

  • the names of centres must be prefixed by ‘UKRI AI Centre for Doctoral Training in’
  • the summary section should contain an overview of the research area of the centre, the need for the researchers that the centre will produce, and the approach that will be taken in a clear concise fashion appropriate for a scientific generalist
  • all other Je-S sections (objectives, for example) should also be completed but note that project partner information should not be provided
  • the duration of the grant should be 102 months
  • in the summary of resources required for project section, place a 0 in the ‘directly incurred’, ‘directly allocated’ and ‘indirect costs’ and put the total requested from UKRI under ‘exceptions’

Applicants should not use the ethical information section on the Je-S form at the outline stage. This information will only be required at the full proposal stage.

You can save completed details in Je-S at any time and return to continue your application later.

Once you have completed your application, make sure you ‘submit document’.


UKRI must receive your application by 23 February 2023 at 4pm.

You will not be able to apply after this time.

The standard duration for which the outline stage is open has been extended by 2 weeks to allow for the Christmas holiday period.

Your host organisation’s administration is required to complete the submission process. You should allow sufficient time for your organisation’s submission process between submitting your proposal to them and the funding opportunity closing date. You should ensure you are aware of and follow any internal institutional deadlines that may be in place.


All attachments must be completed in single-spaced typescript in Arial 11 or other sans serif typeface of equivalent size, with margins of at least 2cm. Arial narrow and Calibri are not allowable font types.

Text in embedded diagrams or pictures, numerical formulae or references can be smaller, as long as it is legible. Text in tables and figure labels not within embedded diagrams or pictures should be at least 11 point.

We recommend that all attachments are uploaded into Je-S as Adobe Acrobat files (PDF) as uploading word documents can result in layout changes to the document. Also, as Je-S does not support all Microsoft Office Word font types, unsupported fonts will be replaced, possibly resulting in layout changes to the document.

Please be aware that converting to PDF can alter the formatting and result in layout changes, for example, converting from LaTeX to PDF can add small serifs or alter font size. You should ensure documents converted to PDF still meet the formatting guidelines outlined prior to submission.

UKRI will reject before peer review all proposals which do not conform to these formatting rules, with no exceptions made.

Your application must also include the following attachments.

Outline case for support

This attachment should be no more than 3 sides of A4. The case for support should cover all aspects of the assessment criteria. Use the following section headings:

  • centre vision
  • student training experience
  • centre management and pastoral care
Cover letter

This attachment should be no more than 1 side of A4. This letter will only be seen by UKRI and will not be shared with external parties. The letter should:

  • indicate which priority area or areas the application is applying against
  • highlight anything that has been discussed and agreed with UKRI staff beforehand
Additional information form (other attachment)

You are required to use the form provided.

Download the additional information form template (XLSX, 29KB).

For more information on this attachment, read additional information guidance (PDF, 176KB).

Outline costings

At the outline stage, all UKRI contributions should be combined and indicated within the ‘exceptions’ field of the Je-S form. The UKRI contribution to eligible costs will be funded on awards at 100%. Estate and indirect costs will not be funded on these awards.

All costs (including stipends and fees) should be calculated at current rates with no inflation over the grant duration included. UKRI will apply an indexation rate to successful applications when issuing awards.

Costs should not be included to support students outside the CDT cohort, supported by funding from other sources. Where a central cost is incurred by the CDT (such as developing a new training course principally for the CDT students) these ‘aligned’ students can (and are encouraged to) benefit from these.

However, additional ‘per student’ costs such as conference fees, facility access fees, travel, and subsistence for these students should not be included. UKRI expects such support to be provided from the source of the student’s support for example, the DTP or an industrial sponsorship award.

Download the additional information form template (XLSX, 29KB).

Full proposal stage

Only applicants who were successful at the outline stage of this funding opportunity will be invited to submit a full proposal. All other applications will be rejected.

UKRI may require attendance by a representative of the CDT applicant team at a meeting between outline and full proposal stage. The aim of this meeting would be to facilitate engagement between proposed CDTs and potential partners.

Additional project partners may be added between outline and full proposal stages.

There should not be other substantive changes from the centre described at the outline stage.

This page will be updated with specific information about how to apply, guidance, and details of full proposal assessment criteria after assessment of outline proposals.


UKRI must receive your application by 13 July 2023 at 4pm.

You will not be able to apply after this time.

Ethical information

UKRI will not fund a project if it believes that there are ethical concerns that have been overlooked or not appropriately accounted for. All relevant parts of the ‘ethical information’ section must be completed.

Guidance on completing ethical information on the Je-S form.

Guidance for project partners

Outline stage

At this stage statements of support are not required. Instead, applications will need to detail the co-creation of the bid by the most significant partners (within and between organisations, and with project partners as appropriate) as part of the case for support.

You will not be able to record project partner details on the Je-S form at this stage.

Full proposal stage

More guidance on the expectations for project partner statements accompanying full proposal applications will be provided at a later date but brief information about requirements are indicated below.

At the full proposal stage, project partner commitments should be detailed on the Je-S form and reflected in statements of support from each partner. Statements of support should detail the importance of the research training provided by a CDT to the partner as well as how the involvement of the partner benefits the training experience of the students.

If you commit to being a project partner at application stage on more than 1 proposal and those CDTs are successful then it is expected that all partnerships will be committed to.

How we will assess your application

Assessment process

A 2-stage assessment process will be used. The assessment of individual applications and the balance of the training landscape across the AI area will be taken into account when making decisions at both the outline and final stage.

Stage 1: outline proposals

Panel meetings to consider outline proposals and decide which applicants will be invited to submit full proposals are scheduled for the week beginning 24 April 2023. Applicants will be informed of the outcome the week commencing 8 May 2023.

The makeup of these panels will be decided once the population of outlines is known and include participants from a variety of disciplines across UKRI’s remit. Panel members will be drawn from the academic, training management, and user base within the UK and internationally. They will be assigned to the most appropriate panel based on the coverage required.

Outline proposals will be against the assessment criteria below. Based on the strength of evidence provided against the assessment criteria, panels will be asked to rank outline proposals. Once the ranking has been finalised, the panel will be asked to separate the ranked list into a number of bands (groupings which represent proposals of a similar quality).

In deciding which applications to progress, UKRI will consider the number and balance of applications across the portfolio, starting with the highest band. While considering the balance, UKRI may decide to progress an application banded lower than another providing a quality threshold is met. The ranking information may also be used to aid decisions. For example, to distinguish between applications from the same area and in the same band where it is not desirable to progress them all.

Outline proposals will be tensioned across the various panel meeting lists to ensure that those invited to submit a full proposal represent equivalent quality.

Successful applicants will be invited to submit a full proposal. When deciding which applications should progress, UKRI will consider the balance of proposals across the breadth of the priority areas in addition to the assessment of the individual proposal. We anticipate that we will invite no more than twice as many full proposals as we expect to fund.

A list of outlines which have been invited to submit full proposals will be published to facilitate engagement by additional potential partners during preparation of the full proposal. Principal investigator name, Centre for Doctoral Training (CDT) title and the Joint Electronic Submission (Je-S) system summary will be published.

UKRI reserves the right to move applications from this funding opportunity to the Engineering and Physical Sciences Research Council (EPSRC) CDT funding opportunity after the outline assessment, and vice versa, should an application better fit the scope of the other funding opportunity.

In the event of this funding opportunity being substantially oversubscribed as to be unmanageable, UKRI reserves the right to modify the assessment process.

Stage 2: invited full proposal

Full proposals will be assessed by expert interview panels, there will be no postal peer review stage. Interview panels will consider all assessment criteria.

This page will be updated with specific information about the assessment of full proposals after the assessment of outline proposals.

It is expected that interviews will take place during the week commencing 11 and 18 September 2023. Interview panels will comprise of members with a range of backgrounds and expertise.

Outcomes of the interviews will be announced by end October 2023.

Assessment criteria

Outline proposals

Outline applications will be assessed against the following criteria (these are equally weighted):

  • fit to call
    • centre vision and alignment with priority areas
    • plans for delivering the vision, including appropriateness of research environment to enable this
    • appropriateness of the skills of the CDT students at the end of their training
    • national need for students trained in area proposed
  • centre management and pastoral care
    • ability of the applicant team to deliver the CDT
    • diversity of the applicant team, including career stage and background. This includes non-academic team members
    • student supervisory capacity of the host and partner organisations
  • student training experience
    • approach to cohort training and added value of CDT
    • plans for contributions by partners to student training
    • preparation for diverse and flexible career paths

Full proposals

Full proposals will be assessed against the follow criteria:

  • quality of the student experience
  • research training environment
  • inclusive research culture
  • added value
  • resources and management

Additional details for each of the assessment criteria will be provided when this page is updated following assessment of the outline proposals.


Outline stage

Only where directed to do so by the outline panel will successful applicants receive feedback specific to their application. We will not be able to provide feedback to unsuccessful applicants of the outline stage.

Full proposal stage

Feedback will be provided by the interview panel. This will accompany results notifications where possible.


The content of applications will only be shared with UKRI staff and peer reviewers.

Outcomes of both outline sift and full proposal interview panels will be shared through EPSRC’s public facing investment information systems such as the Grants on the Web (GoW) database and UKRI’s Gateway to Research. Information is published on GoW shortly after the panel meeting.

Outline stage

GoW will display the results of the individual outline panels. The only information that will be published on GoW is the number of full proposals that have been invited, and the number that were declined.

In addition to GoW, for successful outline proposals the named investigator, organisation, and Je-S summary section information will be published to facilitate engagement with potential additional partners. Other application content and assessment material will be confidential.

Full proposal stage

GoW will display the results of the individual interview panels. The rank order list information will be published.

For successful full proposals, the summary, organisation, project partner, and named investigator information will be shared. Other application content and assessment material will be confidential.

For unsuccessful proposals, the only information that will be shared is the grant reference number and its rank. The content and assessment of unsuccessful proposals will be confidential, including details of the organisations and applicants involved.

If a proposal is rejected prior to the panel meeting no information will be published on GoW.

Where the panel requests for an applicant to receive feedback, this will only be shared with the applicants and the lead organisation.

Read UKRI’s privacy notice.

Contact details

Get help with developing your proposal

For help and advice on costings and writing your proposal please contact your research office in the first instance, allowing sufficient time for your organisation’s submission process.

Ask about this funding opportunity


Get help with applying through Je-S



01793 444164

Opening times

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Additional info


In the UK, the significant growth in the capabilities and applications of AI technologies has led to their exploitation and use across a broad range of sectors including:

  • health
  • finance
  • security
  • defence
  • life sciences
  • transport
  • communications
  • manufacturing

The strength and importance of this sector in the UK has been recognised in a number of government commissioned reports and review, including:

The government has taken steps to act on the recommendations in these reviews through the 2018 AI Sector Deal, and the publication of the National AI Strategy. As identified by many, if not all, of these reports and strategies, there is intense global competition for advanced skills to develop AI.

The need for skills training in AI is not limited to training individuals who have the high level computational and mathematical skills to develop new technical approaches, but also to training cross-disciplinary experts who can understand the applications of this technology and work to employ it effectively and safely across a wide range of sectors.

This further investment in AI Centres for Doctoral Training (CDTs) builds upon the 16 existing centres funded in 2019. The centres will cover the breadth of AI and its application, bringing novel AI development together with strong domain knowledge.

Through this funding opportunity UKRI will support centres of excellence in research training.

These centres will deliver the next generation of internationally excellent doctoral researchers in AI to meet the needs of academia, industry and other employers. We aim to:

  • fund a balanced portfolio of CDTs that are aligned to identified skills needs for the UK in AI
  • produce highly skilled and talented researchers, and future leaders, by funding world leading innovative centres that are aligned to major research strengths
  • support high quality doctoral research training environments led by robust leadership teams to train internationally competitive doctoral students through a cohort training approach
  • deliver student training activities which enable students to gain broader skills than other doctoral training routes may provide
  • address user skill needs by actively engaging and co-creating training provision with the UK’s strong industrial and user base
  • increase diversity within the field of AI by training a diverse cohort of the next generation of AI researchers

In particular we seek to:

  • ensure a forward-looking, ambitious portfolio of AI research training which makes a positive difference for the UK
  • protect the UK’s long-term AI capability and foster an expansion of multidisciplinary research
  • secure leverage in order to maximise the benefit of public funds
  • train the next generation of UK leaders for industry, research organisations and elsewhere

Through continuing to invest in increased numbers of highly trained skilled people in AI this investment aligns strongly with the UKRI strategy 2022 to 2027, where AI is highlighted as a priority area in securing UK strategic advantage in outcomes and impacts, and a commitment to support delivery of key sector strategies such as the UK government AI Strategy.

In particular, this will be achieved through:

  • supporting interdisciplinary skills and capacity
  • providing new ideas that are critical to address complex challenges
  • increasing the power of research through collaboration and partnership
  • delivering research excellence
  • utilising state of the art infrastructure within the university sector and relevant institutes

CDTs are one of numerous routes by which UKRI supports doctoral training. CDTs are complementary to other routes and we anticipate that much of the need for doctoral students will continue to be met by, for example, doctoral training partnerships.

Responsible innovation and trusted research

UKRI is fully committed to develop and promote responsible innovation. Research has the ability to not only produce understanding, knowledge and value, but also unintended consequences, questions, ethical dilemmas and, at times, unexpected social transformations.

We recognise that we have a duty of care to promote approaches to responsible innovation that will initiate ongoing reflection about the potential ethical and societal implications of the research that we sponsor and to encourage our research community to do likewise.

The CDTs will be required to embed principles of responsible innovation and those of trusted research throughout their activities. They will be expected to engage with the relevant regulatory bodies where concerns may arise under the National Security and Investment Act. Aspects of bias, privacy, security and ethics should be considered where appropriate.

Grant additional conditions

Grants will be awarded under the standard UKRI terms and conditions for training funding.

UKRI reserves the right to modify or include additional conditions before grants are awarded.

Details of grant additional conditions will be published on this page following assessment of the outline proposals.


UKRI held a webinar to support this funding opportunity on 13 January 2023.

View the webinar slides (PDF, 814KB).

Read the webinar outputs (PDF, 194KB).

Watch the webinar recording.

Supporting documents

Equality impact assessment (DOCX, 72KB)

Additional information guidance (PDF, 176KB)

Additional information form template (XLSX, 29KB)

This is the website for UKRI: our seven research councils, Research England and Innovate UK.
Let us know if you have feedback or would like to help us test new developments.