AI hubs
The hubs that are funded through this funding opportunity will be critical mass investments that are expected to form connections to the wider AI community and research and innovation ecosystem. They will have a core mission and sets of activities and objectives in either AI for real data or AI for scientific and engineering research.
While it is expected that the initial submission will contain a core leadership team, collaborative founder stakeholders and plans for initial work programmes, it is also expected that these will:
- evolve and expand over time
- flexibly allocate resource and effort to emergent problems
- collaborate with other hubs, investments and groups that are working on similar problems
- bring in additional partners and interested parties
Funded hubs under this programme will be expected to address the following.
World-class fundamental research in AI
Deliver world class fundamental research in AI, that is co-created with stakeholders from other disciplines, backgrounds and regions against real-world research problems. They will build capability and capacity around working with, and learning from, complex data and datasets, delivering a wide range of outputs and impact for the UK society and economy.
Within AI for real data, it will be expected that this will lead to application of AI on real-world use cases within the lifetime of the hub. In AI for scientific and engineering research, work will focus on accelerating the adoption of new AI capabilities across research domains, driving leadership in focused discipline areas, and facilitating the knowledge exchange of applied AI across disciplinary boundaries.
Engage with key stakeholders
Engage and include key stakeholders, including:
- the UK wide national and international research community (in both AI and across the application areas of the hub)
- policymakers
- government departments and bodies
- industry and businesses
- non-governmental organisations
- third-sector
- funders of research
- users of the research to establish a UK focal point for activity around their strategic area
Over the lifetime of the hub, it is also expected that it will form new cross-disciplinary partnerships across the engineering, physical, and computational sciences or across the AI community and with owners of real-world data.
Inclusivity
Be inclusive. Each hub will coordinate and collaborate across their relevant UK research communities and should be responsive to the wider stakeholder and investment landscape, maximising the value of this investment through alignment to other strategic activities, either existing or new. Particular consideration should be given to the inclusion of, and connectivity to, local and regional stakeholders.
Working with other funded activities
Work with the other funded activities (including other hubs funded through this funding opportunity) as a cohort to further data science and AI research, innovation, and application, collaborate to influence policy and act as a focal point and ambassador for the community.
Healthy, diverse and inclusive AI talent and skills pipeline
Support the development of a healthy, diverse, and inclusive AI talent and skills pipeline. Consideration should be given to the advancement and training of those engaged in the hub from every career stage and towards how any skills programme can be offered more broadly to enhance digital skills in the broader community. This could include the provision of skills training, supporting research software engineers, and setting expectations around data and software management.
Structure of AI hubs
A typical hub will comprise of (but is not limited to):
- a virtual or physical centre which is multi-institutional but based around a lead research organisation
- a hub director (academic) with a proven track record of managing large investments and excellence within their discipline or sector
- a wider leadership team, representative across the different disciplines involved in the hub, from varying career stages with a track record of excellence within their disciplines. It is expected that this team will be diverse against protected characteristics
- a small coordinating management body (which includes a full-time hub manager and a full-time business engagement manager) and an administrative team that will ensure that the programme runs efficiently
- a named lead from one of the host institutions (academic or otherwise) for knowledge transfer and for external communications, whose role will include coordinating knowledge exchange between the hub and the wider landscape
- postdoctoral research assistants (PDRAs) distributed across the project. Funding cannot be requested from these grants for PhD studentships or related funding. However, students funded from other sources can be incorporated into the broader project plan, provided that PhD students’ work is not part of the critical path of the hub’s research
- appropriate advisory and governance structures, including as a minimum, an independent advisory board which should meet at least annually and include key academic, industrial, relevant policy officials and other stakeholders. It is expected that a UK Research and Innovation (UKRI) representative will sit on this advisory board, who will be appointed by UKRI. Provision of the precise and full membership of such a board will not be required at point of application
It is expected that management of hubs will require more investigator time (whether for the principal investigator or distributed across the team) than standard UKRI grants.
Principal investigators will be expected to participate in broader UK AI ecosystem discussions with UKRI and other governmental stakeholders and participate in events.
The expectation of a dedicated project manager reflects the need for coordination across the hub and with the AI ecosystem, enabling the required interdisciplinary, end-user focused approach and the facilitation of engagement with users of the research.
As part of the management process, hubs will be expected to set an appropriate statement of objectives and internal key performance indicators (KPIs) focused on key outputs and outcomes within six months of the hub grant starting. KPIs should be appropriately set against baselines, to be considered at the start of the hub.
You are expected to have a clear plan for supporting diversity, in a broad sense (for example, protected characteristics and career background). It is anticipated that proposals will evidence a strong commitment to supporting the development of researchers (including early career researchers) across the hub and its activities. Activities focused on early career researchers and wider capacity building including for stakeholders will be welcome.
While hubs should propose an initial research programme which will begin to tackle the challenges of the hub itself, it is envisaged that the hub will be able to reallocate funds across existing and new partners to pursue new lines of research or alter research plans to meet emergent demands, linked to their missions and objectives. In addition, hubs can apply for a flexible fund (up to £1 million) which can be used for:
- impact activities including engagement with small and medium enterprises
- engagement and collaboration outreach across key disciplines and sectors, with policy officials, and to the public and internationally if appropriate. This may include incorporating new partners into the hub or working to embed the hub within its local regional strengths
- the translation of research outputs and tools to relevant end-uses
- retaining flexibility within the overall programme of work to allow for the hub to respond to emerging priorities and opportunities
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 endowing chairs, supplementing academic salaries or hosting academics within facilities. It is expected that the leadership team of the hub should contain a demonstrable track record of engagement of this type.
We expect collaborations to build a mutually beneficial two-way relationship based on:
- expertise
- secondments in both directions
- products
- infrastructures
To ensure the awards are inclusive of a variety of approaches and research fields, no specific leverage expectations are being set for eligibility to this programme. The appropriateness and strength of collaborations and plans for each hub to form additional partnerships will be a factor in peer review of proposals.
Clear plans for engaging with new and expanding with existing collaborators over the duration of the hub should be detailed. You are asked to include a user engagement strategy in your outline application which may be extended if you are invited to submit a full proposal. You will have the opportunity to include project partner letters of support at stage two (invited full proposals).
In recognition of the diverse nature of the research and innovation landscape for AI across the UK, and the national role that the awards will play in the EPSRC portfolio, we expect bidders to demonstrate how they will engage and collaborate with stakeholders across all parts of the UK and play into regional, as well as national, innovation and growth strategies.
You should apply for the resources you need to enable strong connectivity with all parts of the UK (England, Northern Ireland, Scotland, and Wales).
Funding streams
This investment will invest in two sets of hubs. It is anticipated that once invited to full proposal, or during the lifetime of the hub, collaborations may be expanded for the core team, potentially including investigators from unsuccessful bids to this funding opportunity.
These two streams will be assessed separately but funding decisions will be taken across the whole portfolio at the point of funding to ensure a balanced portfolio which delivers an investment which can deliver across the outputs desired and outlined in this document.
AI for real data programme areas
The programme is designed to provide the underpinning research that is needed for the development of next generation AI technologies that have the capabilities to meet the demands of real-world applications.
To enable this, EPSRC requires proposals to place an emphasis on key areas of focus which are designed to address specific challenges in an aspect of AI hubs should contain research programmes to address these and include plans for how these will be applied to real world data and problems from collaborators by the end of the investment.
You are asked to clearly highlight your chosen area from the following within your proposal:
- uncertainty quantification
- real-time and dynamic data
- complex data (federated, heterogeneous, noisy, sparse, and multimodal data)
- hybrid AI
To ensure a breadth of research and innovation capability is developed in the UK it is anticipated that successful hubs will be selected such that most or all of the above areas will be funded (and in accordance with the guidance of peer review).
While four areas of focus have been specified, it is for you to determine the broader areas that the hub will focus on in order to address these challenges. Focus should remain on working with real world data, but areas may include (for illustrative purposes only):
- low quality data
- missing data
- noisy data
- real-time data
- small data
- sparse data
- unstructured data
As part of this investment, the hubs will collaborate across the wider AI for real data programme and should be designed and delivered in partnership with relevant end-users, including industry or government (national and, where appropriate, regional, or local).
Successful hubs will be required to develop and execute a strategy for engaging with the wider programme, potential end-users, and stakeholders. Hubs should detail how they plan to develop techniques and demonstrators which are applied to real world use cases or data, with partners, within the lifetime of the hub.
AI for scientific and engineering research programme areas
This investment seeks to support the realisation of the objectives above through the creation of highly collaborative and interdisciplinary hubs that will seek to use AI to do science and engineering differently, enabling for new discoveries and the creation of new scientific knowledge and understanding.
While AI is a powerful tool for analysing complex data sets and automating traditional science, it also has the potential to enable us to do science differently in the future, to enable new discoveries and the creation of new scientific knowledge and understanding, potentially solving a range of hitherto intractable problems.
Across scientific disciplines, AI will play a key role in intelligent use of data, including integrating data collected from different sources under different conditions or at different scales, searching for rare and unusual events, and determining which data to keep and which to discard.
The activity proposed here will invest in new interdisciplinary approaches which will bring the power of AI to bear on world leading research.
To support this, each AI for scientific and engineering research hub will consist of a consortium of academic and industry organisations and will be expected to work collaboratively with a range of stakeholders across the UK’s research and innovation landscape.
Co-creation between the AI community and a science or engineering discipline is essential and should be evidenced in the work packages, leadership team and governance of the hub.
Funding is available to support a number of hubs which combine novel AI development with its application in new methodologies within an aspect of EPSRC remit science or engineering.
To ensure a breadth of research and innovation capability is developed in the UK it is anticipated that successful hubs will be selected such that a range of scientific or engineering areas will be represented in the final portfolio.
You are asked to indicate in your application how you address both development of novel AI and contribute to an area of EPSRC-funded science or engineering. The following are example areas, provided just for illustration purposes, for which applications will be accepted:
AI for chemistry
Using AI as a tool to explore chemical space to facilitate new insights into the behaviour of molecules, systems, and chemical reactions.
Applications for a hub in this area must focus on accelerated discovery and the creation of best-in-class reactions with greater atomistic efficiency and a renewed ability to explore new chemical space for form and function is expected.
It is expected that new methods represent a step change in the approach to design, testing and integrated feedback loops, leading to faster transitions from theory, design, synthesis, and validation.
AI for engineering
Utilising advanced AI to enable a step change in an aspect or type of engineering, for example manufacturing for a circular economy or AI as applied to systems engineering or urban systems research.
Applications for this hub should focus on AI tools that provide actionable insight and take a whole systems approach by focusing on how novel tools can be utilised at-scale and across the value chain. Applications should consider how different parts of the system influence each other and embedding consideration of the risks, costs and trade-offs associated with different materials, technologies and approaches.
Particularly, circularity and sustainability of engineering approaches should be considered, (for example manufacturing for the circular economy) delivering digitally enabled, prosperous and resilient UK sectors with circularity at their core.
AI for materials science
A focus on AI tools for accelerating discovery of novel materials and properties, including their design, characterisation, and potential manufacturing. The hub should address the differing challenges of using AI with a selection of materials and property types, as well as across a range of length scales, to deliver a step change in UK research into materials that will enable sustainable economic and environmental futures while being sustainable throughout their lifecycle.
AI for physics
AI to better our understanding of quantum phenomena, condensed matter physics, or physical science approaches within biophysics. AI which can be applied to expand understanding of interatomic potential and field, electronic or superconducting properties, or which can be combined to accelerate the development of quantum technologies from the base scientific discipline.
Applications across any science or engineering area should consider the implications of overlaps and synergies with other areas funded under this funding opportunity, as well as underpinning concepts of responsible innovation, intellectual property, and national security. You will also be expected to outline how your chosen area will contribute to the realisation of the science and engineering challenges outlines in the EPSRC delivery plan.
As part of this investment, the hubs will collaborate across the wider AI for scientific and engineering research programme and their wider relevant ecosystems. They should be designed such that they consider the overlaps and synergies with the other programme areas.
Proposals should highlight why their suggested hub is nationally important, and how their interdisciplinary approach will enable adoption of new AI capabilities across research domains, drive leadership in focused disciplines areas, and facilitate knowledge exchange of applied AI across disciplinary boundaries to enable a step change in scientific discovery and research methods.
Involvement of The Alan Turing Institute with the AI hubs
As the UK’s national centre for data science and AI, The Alan Turing Institute is well-positioned to work with successful projects from this programme. The exact nature of the institute’s interaction with successful projects will be dependent on the details of each project. The Turing will not be offering specific support (this includes offering letters of support) to individual applications.
It is expected that all hubs will either have, or will develop, links with the Turing as part of facilitating the flow of ideas and methods across the AI ecosystem, but these will not be mandated. Previous engagement is not required at the point of application, nor will it be considered as part of the peer review process.
Funding available
The total EPSRC funding available for this opportunity will be up to £60 million to fund up to six hubs.
The total fund for this funding opportunity is £75 million, EPSRC will fund £60 million of the total (80% FEC).
The full economic cost of your project can be up to £12 million. EPSRC will fund 80% FEC.
Up to £1 million is available for pump-priming.
Due to the nature of the programme, there will be additional requirements on reporting, monitoring and evaluation, and grant extensions. This will be reflected in the grant additional conditions, and those funded will need to comply with them.
Costs
Resources may be used for research expenses including:
- UKRI-funded research facilities. Please note that if you plan to use a major facility in your research, such as those funded centrally by EPSRC or a European facility, contact the facility before applying to EPSRC to check if your proposed research is feasible, and obtain a technical assessment if the Joint Electronic Submission (Je-S) system marks it as required
- travel
- research technical support including research software engineers, data scientists, postdoctoral research assistants and fellow salaries
- training
- other standard expenses
Resources may also be used for activities that initiate, grow, and maintain collaborations with stakeholders (for example academia, business, government, third sector) such as:
- secondments
- staff exchanges
- regular travel
Although this is not an opportunity designed for significant capital expenditure, equipment over £10,000 in value (including VAT) and up to £400,000 is available through this funding opportunity. All equipment should be fully justified and essential to the mission of the hub.
You should look to use local compute capacity and national facilities where possible. In circumstances where this is not possible, and there is a specific need, compute may be requested.
Smaller items of equipment (individually under £10,000) should be in the ‘directly incurred – other costs’ heading.
Duration
Funding is available for 60 months, and projects must begin by 1 February 2024.
Responsible innovation and trusted research
EPSRC is fully committed to developing and promoting responsible innovation and trusted research.
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
- encourage our research community to do likewise
The hubs will be required to embed principles of responsible innovation and those of trusted research throughout their activities and 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.
Sustainability
UKRI’s environmental sustainability strategy lays out our ambition to actively lead environmental sustainability across our sectors. This includes a vision to ensure that all major investment and funding decisions we make are directly informed by environmental sustainability, recognising environmental benefits as well as potential for environmental harm.
In alignment with this, UKRI is tackling the challenge of environmental sustainability through our building a green future strategic theme, which aims to develop whole systems solutions to improve the health of our environment and deliver net zero, securing prosperity across the whole of the UK.
Environmental sustainability is a broad term but may include consideration of such broad areas as:
- reducing carbon emissions
- protecting and enhancing the natural environment and biodiversity
- waste or pollution elimination
- resource efficiency and a circular economy
EPSRC expects hubs to embed careful consideration of environmental sustainability at all stages of the research and innovation process and throughout the lifetime of the hub.
Hubs should ensure that environmental impact and mitigation of the proposed research approaches and hub operations, as well as the associated project outputs, methodologies developed across science and engineering and outcomes is considered.
Hubs must also seek opportunities to influence others and leave a legacy of environmental sustainability within the broader operations of your academic and industry partners.
Equality, diversity and inclusion (EDI)
As leaders in the community, the hubs will be expected to embed EDI in all their activities throughout the lifetime of the investment.
If funded, this will include identifying the specific EDI challenges and barriers in their own environment and developing a strategy to address these, with reference to EPSRC’s published expectations for EDI.
Hubs must ensure that they request appropriate resources to develop and deliver their EDI strategy effectively. This must include at least one costed staff post with responsibility for EDI (the hub EDI Lead). Hubs should include information on EDI resources (including the mandatory costed staff post for the EDI Lead and any other resources, for example mentoring schemes, training, workshops, and data exercises) in the justification of resources document.
EPSRC does not specify any particular full-time equivalent, salary level or career stage for the EDI lead post. Hubs may decide what is most appropriate for their programme, while giving due consideration to flexible working.
