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Funding for excellent data science and computational science projects with potential to make an impact on health, sustainability, and life science

The Novo Nordisk Foundation focuses on building a strong and internationally competitive life science ecosystem in Denmark. This includes providing grants to research in artificial intelligence, machine learning, statistics, data science, and computational sciences in Denmark.

The Foundation will offer grants with a strong data science component through two programmes:

  • Data Science Collaborative Research Programme and
  • Data Science Investigator Programme.

Both programmes have a scientific focus which encompasses computational sciences more comprehensively than previous data science programmes from the Novo Nordisk Foundation. This includes incorporating projects that utilise simulations and mathematical modelling, particularly relevant in fields such as epidemiology, climate modelling, and materials physics in relation to the transition to sustainable energy sources.

The Data Science Collaborative Research Programme supports data science-driven collaborative research projects within the Foundation’s scientific focus areas. The annual grant budget for this programme is DKK 75 million.

The Data Science Investigator Programme supports excellent independent research leaders with ambitious projects within the field of data science. The programme has separate calls for the Emerging, Ascending, and Distinguished career stages. The combined annual grant budget for this programme is DKK 75 million. See the previous recipients here.

The Foundation also supports initiatives within infrastructure related to data science and computational sciences through the programme Research Infrastructure – Large Equipment and Facilities.

Areas of support

The research proposed for the Novo Nordisk Foundation’s open competition programmes must fall within the following key areas:

  • Development of new algorithms, methods, and technologies within data science, computational science, artificial intelligence (including 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 Novo Nordisk Foundation’s scientific focus areas (see below).

All applicants must clearly show the relevance of their project for potential future application and impact within the Novo Nordisk Foundation’s three focus areas. These are:

  • Health. The activities within this area aim to contribute to improving the prevention and treatment of diseases that threaten global health. This includes preventing cardiometabolic disease, understanding and managing cardiometabolic disease, fighting inequality in health, and strengthening epidemic preparedness.
  • Sustainability. The activities within this area aim to promote knowledge and solutions that help prepare the green transition in society. This includes sustainable and high-yield agriculture, sustainable food for healthy diets, scalable climate change mitigation technologies, and supporting the green transition in society.
  • Life Science Ecosystem. The activities within this area aim to secure a Danish world-class life science ecosystem that will enable us to better manage future challenges. This includes fundamental research as a prerequisite for development, enabling research infrastructures and technologies, translational capacity and societal impact, and education and science capital.

Applicants are welcome to contact the Foundation with questions regarding eligible areas of support.

Procedure

The open competition proposals submitted for Novo Nordisk Foundation are evaluated by the Committee for Data Science, which consists of 10 international experts in the field.

Please consult the Novo Nordisk Foundation calls and guidelines here for in-depth information concerning eligibility and requirements.

For more information about funding opportunities within the data science field at the Novo Nordisk Foundation, please contact: