Interdisciplinary Research

Research Seed Funding

Generating academic interest in sector specific multi-disciplinary projects.

Bayes Centre Seed Funding

Bayes Seed Funding decorative image

Thanks to strategic funding granted by the College of Science and Engineering (CSE), the Bayes Centre was tasked with allocating up to £80,000 in the form of small grant awards to enable University staff to work on commercially relevant activities in the field of data science and AI. These projects could range from developing innovative ideas around data assets, building multidisciplinary opportunities that could unlock industry engagement, to developing upskilling content aimed at professionals.


Applications could be submitted by any member of academic staff from across the University. The normal maximum amount awarded was limited to £5,000, though in exceptional cases they were able to award up to £10,000 if this was justified by the scale of the opportunity the seed funding could unlock. Crucially, for that call, they expected activities to consider the relevance to industry in the development of the project. Projects should have looked to promote interdisciplinary collaboration where possible and focused on using Data Science or AI for the benefit of one or more of the application areas listed below (aligned with the University's Research and Innovation Themes):

  • Exploiting existing data assets and their linkage to enable new research or innovation opportunities;
  • Building multidisciplinary collaborations that can unlock industry funding; and,
  • The development of online teaching capabilities and plans for implementation with a focus on Bayes’ ambition of upskilling the workforce.

Funding decisions were based on the following selection criteria:

  • Interdisciplinary topic, partnerships with industry, and applicant team with relevant track record and clear articulation of use of AI techniques.
  • Clear plans and commitment to follow-on funding opportunities that will be pursued with an emphasis on scale and appropriate risk-reward balance.
  • Clear articulation of activities and deliverables of the development project (e.g. preparation of bid documents, case studies, publicity assets, events, reports).
  • Appropriate resourcing plan and level of resources leveraged in-kind, demonstrating commitment from all contributing individuals and their units.
  • Addressing the Sustainable Development Goals, Equality, Diversity and Inclusion objectives, and the University’s Strategy 2030.
  • Consideration of ethics, research integrity, equality and diversity.


Applications are now open: Bayes Seed Funding. Closing date for applications: 22nd September 2023