RFPs: Data Science Collaborative Research Programme (Denmark)

The Novo Nordisk Foundation Data Science Collaborative Research Programme supports interdisciplinary research projects in data and computational science with applications in life sciences, health, sustainability, agriculture, and technical fields. Grants of up to DKK 40 million fund collaborative projects in Denmark, emphasizing innovation, methodological advancement, and societal impact. Applications are due through the NORMA system, with a two-phase evaluation process including full proposal submission and interviews.

The Data Science Collaborative Research Programme by the Novo Nordisk Foundation (NNF) fosters innovative research collaborations in data science and computational science. The programme aims to strengthen Denmark’s research ecosystem by connecting data scientists with experts from other disciplines, promoting interdisciplinary synergy, and advancing education and training in computational methods.

Objectives of the Programme

The programme focuses on:

• Methodological Innovation: Developing new computational methods, algorithms, or technologies

• Application of Data Science: Using computational approaches in areas aligned with NNF’s strategy, including:

  • Life sciences and health

  • Sustainability and environmental research

  • Agriculture and food systems

  • Natural and technical sciences

• Collaboration & Education: Enhancing interdisciplinary collaborations and supporting data science training and teaching

• Open Science: Promoting reproducibility, data sharing, and transparency in computational research

Funding Overview

• Total Funding (2026 Call): DKK 99 million

• Individual Grants: Up to DKK 40 million, depending on consortium size

• Eligible Expenses:

  • Salaries for scientific and technical staff

  • PhD tuition and stipends

  • Equipment and research infrastructure

  • Data management and software tools

  • Collaborative activities and workshops

  • Publication costs

• Excluded Costs: Overheads, commercial activities, and double funding

Who Is Eligible?

• The main applicant must be affiliated with a Danish institution during the project period

• At least one applicant must be a data science or computational science researcher

• Collaborators: Up to five per proposal, ideally from multiple institutions to strengthen interdisciplinary synergy

• Both method-driven and application-driven projects are eligible, provided they demonstrate novelty, relevance, and impact

Research Focus and Priorities

Applicants can propose projects that either:

1. Advance Computational Methods – Novel algorithms, tools, or methodologies with potential impact on health, life sciences, sustainability, or technical research

2. Apply Data Science to Strategic Domains – Innovative computational solutions to address societal or scientific challenges within NNF’s strategic focus areas

Method-focused projects must clearly articulate their potential applications, while application-driven projects should demonstrate computational innovation in context.

How to Apply / Submission Process

1. Full Proposal Submission: Up to 30,000 characters detailing project aims, methodology, team qualifications, and expected impact

2. Evaluation: International review panel assesses proposals on:

   • Originality and novelty

   • Feasibility and methodology

   • Team qualifications and experience

   • Interdisciplinary and inter-institutional collaboration

   • Alignment with NNF strategic priorities

   • Contribution to teaching, training, and open science

3. Second Phase: Selected applicants participate in interviews for final evaluation

4. Submission Platform: All proposals must be submitted in English through the NORMA system

Evaluation Criteria

• Originality: Innovative approach and research novelty

• Feasibility: Realistic project design and timeline

• Team Strength: Expertise, experience, and complementary skills

• Collaborative Impact: Interdisciplinary synergy and partnership quality

• Alignment: Contribution to NNF strategic priorities

• Educational Contribution: Involvement in teaching and training

• Open Science Practices: Data sharing, reproducibility, and transparency

Common Mistakes to Avoid

• Exceeding the character limit for proposals

• Failing to demonstrate interdisciplinary collaboration

• Omitting evidence of methodological or application novelty

• Including ineligible expenses such as overheads or commercial activities

• Submitting incomplete or incorrectly formatted proposals in NORMA

Frequently Asked Questions (FAQ)

Who can apply for the programme?
Researchers affiliated with a Danish institution, with at least one data or computational science expert on the team.

What types of projects are supported?
Methodological innovation in computational science or data science applications in strategic domains relevant to NNF.

What is the maximum grant amount?
Up to DKK 40 million per project, depending on consortium size.

How many collaborators are allowed?
Up to five collaborators per proposal.

How are proposals evaluated?
Through a two-phase process: full proposal review and interview by an international evaluation panel.

Can commercial activities or overheads be funded?
No, these costs are explicitly excluded.

Where and how should applications be submitted?
Proposals must be submitted in English via the NORMA system.

Conclusion

The Novo Nordisk Foundation Data Science Collaborative Research Programme empowers interdisciplinary research teams in Denmark to push the boundaries of computational and data science. By funding innovative projects, fostering collaborations, and emphasizing education and open science, the programme strengthens Denmark’s research ecosystem while addressing strategic scientific challenges with global relevance.