Waltham Foundation Research Call for Companion Animal Health and Welfare
The Waltham Foundation Research Grants support research that advances understanding of the nutrition, health, behaviour or welfare of companion animals.
For the 2019 grant call, the Foundation is seeking proposals for data science projects, within any life sciences discipline. The call rationale is based on the Foundation’s objective of using data science to improve pet health and the world in which they live – including better veterinary care, data driven policy making and sustainable food for the future. The Foundation is seeking to foster rapid innovations in many areas of data science as it relates to the health and welfare of companion animals, from information management and analytics to data applications.
Preferred topic areas for the 2019 call include:
Enrich publically available data, for example:
The curation of existing data or databases (for example, improving the gene, transcript, or protein annotations of companion animal reference genomes).
New/additional data collection such as adding additional metadata/data points/data types to an existing or planned project in which the new data will be extensive and serendipitous to future analysis.
FAIR-ification of a data source: improving the findability, accessibility, interoperability, and reusability of a data source to enable the second life of data which has tangible value for the community.
Transfer knowledge to the area of Petcare, for example:
Applying an existing or novel application to pet research – e.g. the transfer of generalised models from non-pet data to applications of pet relevance.
Using existing knowledge/data to create a new resource – e.g. semantic analysis of literature to generate pet-relevant knowledge graphs.
Improve research methodologies, for example:
Algorithm development, i.e. fundamental research into improving the predictive accuracy or efficiency of an analytical method with a potential beneficial application within pet research.
Integration of data: methodological improvements that ease or benefit the interoperability of disconnected data types – e.g. unsupervised methods that use inference to connect responses between multi-omics data using Bayesian, factorisation, network–based, or other analytical approaches.
The principle investigator should be based at a university or academic institution that provides appropriate research facilities. There is no restriction on the location of the applicant’s institution.
Grants of up to US$25,000 are available to fund projects for a period of up to two years.
Guidelines and application forms are available for download from the Waltham Foundation website.
Applications for the 2019 Call should be submitted by the deadline of 1 May 2019.
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