Fellowship programme


Research scope

To be an eligible candidate for the DDSA Fellowship Programme, applicants’ research topics must adhere to either the research scope of the Novo Nordisk Foundation Data Science Initiative (Box 1), or the research scope of VILLUM FONDEN (Box 2):

Box 1: Scientific scope of the Data Science Fellowships financed by the Novo Nordisk Foundation (NNF)

To be eligible for a scholarship financed by the NNF, the research activity must be within the scope of the NNF Data Science Initiative, which covers the following 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 NNF’s scientific focus areas: Biomedical and health science, life science and industrial applications promoting sustainability, as well as natural and technical sciences with potential application in biotechnology or biomedicine.

For projects mainly concerned with methods development, it is important that the applicants argue convincingly for potential application and impact within the Novo Nordisk Foundation’s scientific focus areas. The potential application could be beyond the project period. Vice versa, projects that have their primary focus on the application side 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.

In general, projects without potential applications within the NNF’s scientific focus areas and projects with no novelty in terms of development or application of data science methods will not be eligible for funding.

Box 2: Scientific scope of the Data Science Fellowships financed by VILLUM FONDEN

To be eligible for a scholarship financed by VILLUM FONDEN, the research activity must be within data science or the application of data science to topics in technical science, natural science, humanities or social science or a combination of these. The Foundation is favorably inclined towards applicants coming from other fields and wishing to pursue a PhD within data science. The project may combine a core of computer science with one or more application domains (cf. figure).