Artificial Intelligence/ Machine learning and Medicine

The aim of the Rosetrees 2022 Interdisciplinary Award is to encourage collaboration between Clinicians/Scientists and experts in Artificial Intelligence/Machine Learning. Rosetrees hope that the merging of skills and experience in these areas will lead to innovative research that addresses unmet clinical needs. Applicant proposals must include details on how artificial intelligence and machine learning can result in patient benefit within 5-10 years.

Projects that address logistical problems within the NHS that will result in more efficient services, reduce costs and/or improve patient experience are of interest.

Applications open: NOW
Internal Expression of Interest deadline: Friday 4 March 2022
Notification of funding decision: October 2022
Grant duration: 3 years
Funding amount: £300,000

Funding

• The interdisciplinary award is for £300K paid over 3 years. This funding can be used to support any aspect of the proposed research. Rosetrees will fund directly incurred costs associated with the project, including salaries, consumables and other running costs. Directly allocated costs, indirect costs or PhD tuition fees will not be covered. Travel costs (max. £1000) will be considered.
• Funding can be used to fund salaries for post-doctoral research associates, research technicians and research assistants. In special cases, Rosetrees may consider funding PhD stipends. In these cases, the prospective PhD student must be embedded within a larger programme of research (e.g. a clinical trial or a programme grant) and there must be a clear case that Rosetrees support will provide additional impact.
• Applications are generally outstanding quality and selecting a winning award is very challenging. In recent years, the Rosetrees selection panel has selected a winning project which has been awarded £300K. They have also identified very high-quality applications that were awarded up to 50% funding (£150K) on the condition that the applicants were able to provide matched funding of £150K. Rosetrees encourage all applicants to consider additional funding sources in advance so that if selected as a runner-up, they are able to start their project as soon as possible.  The number of projects awarded £150K is flexible, depending on the quality of the applications and their ability to secure matched-funding of £150K.

Eligibility

• Applications should be interdisciplinary and clearly represent collaboration between medicine and AI/ML. They can relate to any disease or medical condition that affects a significant proportion of the population.
• The 2 lead applicants (medicine and AI/ML) should be tenured academics within the host institution. Only one ID award application can be made per host institution. However, in exceptional circumstances, Rosetrees can consider applications from two departments in two separate host institutions if, for example, one of the institutions does not host a medical school. In these cases the lead institution will be the one hosting the medical department and will be the only application allowed from that institution. Please contact Rosetrees in advance if more than one institution is involved.

Applications

• The University of Manchester’s internal application phase requires interested parties to complete the Expression of Interest form and email it to Matthew Harrison on or before 3pm on the 4th March 2022.
• A cross-faculty panel will review these submissions reviewers and assess a range of criteria, such as: experience and track record of the lead applicants; importance of the research; the interdisciplinary nature of the project; how well placed the researchers are to carry out the study; impact of the research and potential for translation and future clinical benefit; whether the scale and nature of funding is appropriate.
• The panel will agree which applications to support by 15th March 2022.
• All those who have expressed an interest will be notified of the outcome by 21st March 2022.

Contact

For general enquiries, please contact Institute for Data Science and AI Manager, Matthew Harrison.

More details are available at the Rosetrees Trust website.

Related