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Novo Nordisk Foundation launches new data science and AI initiative

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Novo Nordisk Foundation awards DKK 138 million under its new data science and artificial intelligence initiative.

“Data science is an important driver in all modern research. Society and the research community definitely need more specialists in this area, and with this initiative we want to contribute to Denmark being at the forefront of development – also 10 years from now,” says Birgitte Nauntofte, CEO, Novo Nordisk Foundation.

A total of DKK 138 million

The Data Science Initiative comprises three programmes that collectively support the establishment of research within data science. This will be carried out by establishing national infrastructure and research collaborations and through a research leader programme that will create a very attractive career path and will help to educate and train additional specialists in this area, states the NNF.

“DKK 65.5 million for eight Investigator Grants, DKK 45 million for ambitious collaborative research between data scientists or between data scientists and researchers in other scientific areas, and DKK 27.9 million for two projects within research infrastructure.”

A total of DKK 138 million has been awarded; DKK 65.5 million for eight Investigator Grants, a programme for research group leaders (each researcher is receiving a grant of up to DKK 10 million), DKK 45 million for ambitious collaborative research between data scientists or between data scientists and researchers in other scientific areas, which collectively will create synergy in research that would not have been possible individually, and DKK 27.9 million for two projects within research infrastructure. The funding is for establishing and developing world-class national infrastructure within data science (such as supercomputers, hardware, databases and technical personnel).

Collaborative research projects

The Novo Nordisk Foundation has awarded a total of DKK 45 million for two major research collaborations that will seek answers to important scientific questions across disciplines and geographical units. This will be achieved through the Data Science Collaborative Research Programme, which aims to support excellent and ambitious ideas stemming from data science – a research area that includes artificial intelligence, machine learning and managing large data sets.

“One project, Machine Learning Methods for Data-driven Discovery of Antibiotic Resistance Plasmid Dissemination and Evolution, seeks to improve understanding of how antibiotic resistance occurs.”

One project, Machine Learning Methods for Data-driven Discovery of Antibiotic Resistance Plasmid Dissemination and Evolution, seeks to improve understanding of how antibiotic resistance occurs. Specifically, the researchers will use artificial intelligence and machine learning to acquire more knowledge on plasmids, tiny DNA fragments that can transfer genetic properties, including antibiotic resistance, between bacteria.

“The second project, Center for Basic Machine Learning Research in Life Science, will carry out collaborative research on using machine learning to solve fundamental problems in the life sciences.”

The second project, Center for Basic Machine Learning Research in Life Science, will carry out collaborative research on using machine learning to solve fundamental problems in the life sciences. The Center will be based at the Department of Biology of the University of Copenhagen and will include leading researchers within machine learning from the Department of Applied Mathematics and Computer Science of the Technical University of Denmark and the Department of Computer Science of the University of Copenhagen.

Two projects within research infrastructure

One of the two projects within research infrastructure is the National Health Data Science Sandbox for Training and Research. It will be based at the Center for Health Data Science, Faculty of Health and Medical Sciences, University of Copenhagen. Researchers throughout Denmark will collaborate on building a national Sandbox infrastructure that will provide students and researchers with access to synthetic health data in a specially designed environment.

“Researchers throughout Denmark will collaborate on building a national Sandbox infrastructure that will provide students and researchers with access to synthetic health data in a specially designed environment.”

Users of the Sandbox will have access to the actual data and anonymized synthetic data and tools, computer programmes and computing power from supercomputers, similar to working on a project with the actual health data. The users will instead find themselves in the protected test area of the Sandbox that can ease the transition to working with the actual health data.

“The purpose of the second project, The OpenNeuroPET Archive – A Molecular Neuroimaging Archive, is to establish an open-access platform that can systematically and uniformly process and archive data from brain imaging.”

The purpose of the second project, The OpenNeuroPET Archive – A Molecular Neuroimaging Archive, is to establish an open-access platform that can systematically and uniformly process and archive data from brain imaging. This database will enable researchers worldwide to share data to advance brain research and medical imaging technology. It will be specifically designed so that the data sharing complies with the General Data Protection Regulation of the European Union.

The new infrastructure will enable researchers to collect and reuse data from neuroimaging carried out using positron emission tomography (PET), a method for measuring the quantity and location of specific molecules in the brain.

Investigator Grants

Over a 5-year period, eight researchers will investigate challenges in which data science plays a crucial role by developing artificial intelligence, bioinformatics, statistics and other things. The eight researchers are at different stages of their careers, and each must develop and streamline data science methods for solving complex problems in biomedicine, health, sustainability, biotechnology and research in the natural and technical sciences.

The grant categories are: Emerging Investigator, Ascending Investigator and Distinguished Investigator, which target research leaders at various career stages to support attractive career paths for the most skilled specialists within data science.

“By awarding these eight grants for researchers at different career stages, the Novo Nordisk Foundation wants to emphasize the importance of attracting and retaining data scientists in academia.”

“By awarding these eight grants for researchers at different career stages, the Novo Nordisk Foundation wants to emphasize the importance of attracting and retaining data scientists in academia. Several of the projects will lead to the development of fundamental algorithms and understanding within physics, mathematics and other subjects. These will form a solid foundation that is inherently relevant and also necessary to develop data science with the broadest possible applications. These application areas range from developing medicine and data-driven patient care to conducting research to develop sustainable solutions to climate challenges,” says Lene Oddershede, Senior Vice President, Natural & Technical Sciences, Novo Nordisk Foundation.

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