The Gnatwork has funding available to pump-prime collaborative studies that bring together researchers from around the world and across vector groups (blackflies, sandflies, biting midges).
Our second pump-prime funding call, Transformative Science, will fund projects that investigate specific areas of preliminary research that are sufficiently novel to lead to future, large-scale funding. This call is worth £300 000, with a maximum cap of £100 000 for a single project (smaller scale projects are encouraged). A maximum of four-six projects will be funded, of six, nine or twelve months in duration. We are looking to support projects which link to researchers in countries receiving official development assistance (ODA) and generate data to underpin future external funding applications.
Our Transformative Science call is now open!
There is a two stage application process. Applicants will be first asked to submit an expression of interest, which will be reviewed by the Network Management Board. Selected applicants will then be invited to submit a full proposal.
The EOI application form can be found in the sidebar. The closing date for EOI is 7 December 2018, completed applications should be emailed as a PDF to enquiries [at] gnatwork [dot] ac [dot] uk. Please ensure that you read the application guidelines (see sidebar) to ensure that your project meets the required criteria.
What types of projects will the Gnatwork fund?
Applications to the Transformative Science call should be based on innovative research questions and can have a high intrinsic risk. Projects must be relevant to more than one vector group (blackflies; sandflies; biting midges). Areas could include:
- Designing a novel surveillance technique for vectors
- Comparative behavioural studies across the three vector groups (e.g. oviposition; studies of semiochemicals; resting sites)
- Development of novel control methods (including GM-based technologies)
- Novel approaches to mathematical modelling of interventions and/or insecticide resistance
- Trials of vector competence using field or genetically modified pathogens
- Examining the social impact of specific diseases spread by these vector families
- Linking vector occurrence data and taxonomy to mapping of disease occurence
- Machine learning applications