Data Science Initiative
Data Science Initiative
The Novo Nordisk Foundation’s Data Science Initiative has four connected acitivities. Three are open calls with an annual application round in 2020-2022, for which the Foundation has allocated DKK 410 million:
- Collaborative Research Programme: large grants supporting data science-driven collaborative research projects (Grant size is up to DKK 25 million over 5 years). Read more here.
- Investigator Grants: grants for independent data science group leaders at different career stage. The grants aim at creating attractive academia career opportunities for data science researchers (Grant size is up to DKK 10 million over 5 years). Further details can be found under the individual calls (Emerging, Ascending and Distinguished investigators).
- Research Infrastructure Programme: grants to support establishment and operations of national data science infrastructure such as supercomputers, hardware, technical personnel, databases, etc. (Grant size is DKK 5-15 million over 5 years). Read more here.
The fourth activity is funded by Novo Nordisk Foundation in collaboration with VILLUM FONDEN:
- Data Science Academy: The Novo Nordisk Foundation and VILLUM FONDEN are awarding a combined grant totalling DKK 184.3 million to the Danish Data Science Academy – a national academy which will strengthen the training of researchers and interdisciplinary collaboration within data science. The Academy will be established in 2021 and will bring together and strengthen the many actors and stakeholders within academia, hospitals and the business community in Denmark. Read more here.
The initiative is aimed at supporting research where data science is a main driver of the projects, and not merely a support function. In addition, the proposed research must fall within the scope of the NNF Data Science Initiative, which comprises the following scientific areas:
- Development of new algorithms, methods and technologies within data science, artificial intelligence (incl. machine learning and deep learning), data engineering, data mining, statistics, applied math, computer science, big data analytics, etc.
- Applications of data science (as defined above) within the Foundation’s scientific focus areas. Biomedicine and health science, life science and industrial applications promoting sustainability, as well as natural and technical science with potential application within biotechnology or biomedicine.
For projects mainly concerned with data science methods development, it is important that the applicants clearly show the relevance for potential future application and impact within life science, health science, or biotechnology. Vice versa, projects which have their primary focus on application of data science methods must describe and explain the novelty and impact of their data science approach, be it development of novel methods or novel applications of existing methods.