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https://novonordiskfonden.dk/en/projects-and-initiatives/data-science-initiative/

Data Science Initiative

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 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 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 up to DKK 5-15 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.

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 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.