The Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), will initiate a collaboration.
The ultimate goal of the collaboration will be to solve ground breaking research questions and to create synergies across disciplines. The effort will bring together state-of-the-art research infrastructures, research networks and life science/AI/ML competences spread across the country, states SciLifeLab in a press release.
“The DDLS program has just got started in Jan 2021, and we are happy and excited to plan the first ever call for funding from DDLS. To kickstart DDLS, this first call will be in collaboration with WASP, which is very fitting for a data-driven life science program. Engagement of the data science and life science communities is essential for the DDLS program,” says Olli Kallioniemi Director of SciLifeLab and the DDLS program.
World-leading AI researchers
Wallenberg AI, Autonomous Systems and Software Program (WASP), gathers several of the world-leading AI researchers, now counting 40 recruited faculty members and a graduate school with more than 300 ongoing PhD projects. The program has since 2015 provided a platform for academic research and education, fostering interaction with Sweden’s leading companies. The vision of WASP is to promote excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry.
Supporting data-driven life science
The SciLifeLab and Wallenberg National Program for Data Driven Life Science (DDLS) was announced in October 2020 and officially launched in January 2021. Funded by the Knut and Alice Wallenberg Foundation (KAW), DDLS is a 12-year initiative to support data-driven life science in Sweden and change the way life science is carried out, with SciLifeLab as the main host. The program will focus on four strategic research areas, data-driven research in: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and infection biology. The aim of the program is to foster the next generation of life scientists, provide every scientist with knowledge and tools to better analyze data patterns and integrate their data with the global life science data streams, and to create a strong computational and data science base.