Data Science Initiative
The Novo Nordisk Foundation has allocated DKK 410 million to be awarded over the next 3 years to support ambitious research programmes and national infrastructures, offer attractive career paths for data science researchers, and educate more specialists in this field.
The Data Science Initiative has four connected elements of which three will open for applications in early 2020, followed by an annual application round until 2022:
- Collaborative Research Programme: large grants supporting data science-driven collaborative research projects (Grant size is DKK 15-30 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 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 5-25 million over 5 years). Read more here.
- Data Science Academy: The Foundation has the intention to support the establishment of a national Data Science Academy that will develop new educational and networking activities, as well as award a limited number of PhD and postdoctoral fellowships. The academy will be developed during 2020 by the NNF based on input from the data science community in Denmark.
You can find all our grants under “Apply for Grants” in the menu.
Data Science definition and the NNF’s scientific focus areas
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.
Projects where the primary focus is on financial or insurance data, fraud detection, advertisement, social media, social science or humanities, security and mass surveillance, defence, gaming, etc. are considered outside of scope and will not be considered for funding.