Scientific scope of fellowships financed by the Novo Nordisk Foundation

Research proposals which are eligible for funding should address:

1. Development of new algorithms, methods and technologies within data science, artificial intelligence (incl. machine learning and deep learning), statistics, bioinformatics, and other computational sciences (incl. mathematical modelling, simulations, etc.)

and/or

2. Applications of data science and computational sciences to areas of relevance to NNF’s strategy, including life science, biomedical- and health science, public- and global health, infectious disease, sustainability, green transition, agriculture, as well as natural and technical sciences.

For projects mainly concerned with methods development, it is important that the applicants argue convincingly for potential application and impact within NNF’s focus areas. Vice versa, projects that have their primary focus on the application side must describe and explain the novelty and impact of their data- and computational science approach, be it development of novel methods or novel applications of existing methods.

In general, projects without potential applications within NNF’s focus areas and/or projects with no novelty in terms of development or application of computational methods will not be funded in this programme. Projects where the primary focus is on financial or insurance, fraud detection, advertisement, commercial analysis, telecommunication, mass surveillance, defence, cyber security, gaming, etc., are considered outside of scope and will generally not be considered for funding.

Scientific scope of the 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).