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Data Science Collaborative Research Programme 2026

Novo Nordisk Fonden

The Data Science Collaborative Research Programme aims to support synergistic research collaborations rooted in data science and computational science with immediate or potential future applications within areas of relevance to NNF’s strategy.

The goals of the Data Science Collaborative Research Programme are:

To foster research collaborations between data scientists.
To support research collaborations between data scientists and experts in other fields, including but not limited to medicine, biology, biotechnology, physics, chemistry, etc.
To support an excellent academic research and education ecosystem within data science in Denmark.
To advance education and training courses in data science-related topics in Denmark.

Areas of support

Research proposals which are eligible for funding should address:

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

and/or

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 scientific 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.

It is recognized that data science application and maturity will differ between disciplines and applicants within biotechnology and natural sciences are also encouraged to apply.

In general, projects without potential applications within NNF’s scientific 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.

Funding

The total annual grant budget for the 2026 Data Science Collaborative Research Programme is up to DKK 99 million. Each grant can be up to DKK 40 million over up to 5 years.

The maximal size of the grant scales with the size of the collaborative consortia (maximally DKK 14 million for 2 partners, DKK 20 million for 3 partners, DKK 28 million for 4 partners, and DKK 40 million for 5 partners).

Application process

The application process consists of 2 Phases.

In Phase 1, a full application, limited to 30,000 characters (including spaces), should be submitted.
After review and discussion in the committee, the top ranked applicants are invited for Phase 2, in which they will present and discuss their proposed research projects with the review committee at the Novo Nordisk Foundation.

The application must be completed and submitted using the foundation’s application system NORMA that can be accessed via the link “Apply now”.

Please read “Information and Guidelines for Applicants” carefully before initiating the application process. The Guidelines provide essential information on the call and the application content and process.

AI Based Application Success Predictor

1. Strong Strategic Alignment

Successful applications clearly align with the Foundation’s strategic focus areas — especially projects that:

Push forward health and biomedical research,

Advance sustainability and environmental solutions, or

Strengthen the life science research and innovation ecosystem.

Projects outside these core foci are generally not competitive unless they relate directly to one of these themes. Novo Nordisk Fonden

2. High Scientific Quality & Rigor

NNF looks for proposals with scientific excellence and methodological rigor:

Clear hypotheses and strong research design,

Well-justified methods and analytical approaches,

Evidence of feasibility and a credible plan to achieve aims.

This principle applies across research grants, whether in life sciences, data science, or the natural and technical sciences. Novo Nordisk Fonden

3. Societal and Real-World Impact

Funded projects generally articulate:

Clear value to society, such as improvements in health outcomes,

Solutions to societal or planetary challenges,

A credible route from research results to practical impact or policy relevance.

Applications that make the chain from idea → evidence → impact explicit score highly in reviews. Novo Nordisk Fonden

4. Clear Fit with Specific Programme Objectives

The NNF runs many distinct calls (e.g., Challenge Programme, Project Grants in Natural Sciences, NERD exploratory grants, Laureate Research Grants). Each has its own defined aims and criteria, and proposals aligned tightly with those definitions are far more competitive. For example:

Challenge Programme: ambitious, multi-institution consortia addressing major research themes. Discover Pharma

Project Grants: mid-range project support with clearly scoped objectives and deliverables. Novo Nordisk Fonden

Laureate Research Grant: for established biomedical researchers to build and strengthen research groups in Denmark. Novo Nordisk Fonden

Predictor: Carefully tailor your proposal to the specific call’s goals and guidelines.

5. Evidence of Feasibility and Team Capability

Competitive proposals demonstrate:

A research team with relevant expertise and track record,

Institutional support (e.g., host university or research center),

A realistic timeline and resource plan,

Clear management and execution structures.

This shows reviewers that the team is capable of delivering the project to completion.

6. International Collaboration and Leadership (Where Applicable)

Although many programmes remain Denmark-centric, NNF has expanded major calls (e.g., the Challenge Programme) to include international researchers, particularly for collaborations involving Danish partners. Discover Pharma

Predictor: Inclusion of strong international collaborators can strengthen proposals for globally relevant Challenge calls.

7. Clear and Realistic Budget Justification

Budgets must be:

Directly linked to the research activities,

Transparent and realistic,

Detailed enough for reviewers to judge resource needs.

NNF does not cover overhead costs and limits indirect costs to a small percentage of the total budget (e.g., up to 5% for administration). Novo Nordisk Fonden

8. Ethical, Legal, and Quality Standards

All funded research must adhere to applicable ethical, regulatory and research best-practice standards — including research integrity and compliance with local and EU norms. Novo Nordisk Fonden

Predictor: Clearly describing ethical oversight (e.g., IRB, data integrity) increases confidence in the application.

🧠 Additional Practical Strategies

Craft a Compelling Narrative

Explain:

Why the research matters in the context of the Foundation’s goals,

What gap in knowledge or application the project addresses,

How the project will be executed and assessed.

Match the Call Language

Read the call guidelines thoroughly — proposals that reuse the scheme’s own terms and objectives are more intuitively scored as aligned.

Build Consortiums for Big Challenges

For flagship schemes like the Challenge Programme, forming multi-institution consortia with clearly defined roles and complementary expertise greatly strengthens competitiveness.

Highlight Societal Impact and Translation Pathways

Describe potential translational outcomes — not just scholarly outputs — especially for health and sustainability programmes.

📌 Summary: What Reviewers Look For

Predictor	Benefit
Strategic alignment	Ensures relevance to foundation priorities
High scientific quality	Indicates likelihood of advancing knowledge
Clear societal impact	Demonstrates value beyond academia
Fit with specific call	Matches reviewer expectations
Feasible plan & strong team	Reduces risk in execution
International collaboration	Enhances scientific breadth
Detailed budget justification	Shows stewardship of funds
Ethical & quality compliance	Meets foundational standards

Specialties

Data Science

Eligibility Requirements

The main applicant or at least one of the co-applicants must be a data science or computational science researcher. The main applicant can be either a computational researcher (data scientist) or a researcher from a relevant application domain (medicine, agriculture, physics, etc.), who is associated to/employed at a university or institution in Denmark during the project period.

The project may include up to 5 collaborators. The proposed research project should demonstrate synergistic collaboration between different research groups, typically from different institutions/departments and different scientific disciplines. The co-applicant(s) can be anchored in Denmark or abroad.

Sponsor Details

Sponsor Institute/Organizations: Novo Nordisk Fonden

Sponsor Type: Corporate/Non-Profit

Address: Tuborg Havnevej 19 2900 Hellerup

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