Simon Olsson, Associate Professor in Data Science and AI at the Department of Computer Science and Engineering, has been awarded a prestigious ERC Consolidator Grant of two million euros. The funded project, SPETITO, focuses on developing generative AI methods to efficiently simulate the motions of proteins – and then use these tools to design new vaccines.
“Our work aims to explore chemical and biological spaces far beyond what is feasible with classical computational or experimental methods – offering a path to faster drug discovery, novel materials or biomolecules – by combining rigorous scientific principles with modern mAI-based shortcuts,” says Simon Olsson.
Accelerating molecular discovery with AI
Simon Olsson works within the AIMLeNS group (Artificial Intelligence and Machine Learning in the Natural Sciences), where physics, chemistry, biology and advanced AI come together to accelerate discovery in molecular science. The group develops machine-learning models that drastically speed up molecular simulations and make it possible to design new molecules – such as small-molecule therapeutics, biologics or materials – from scratch. In simple terms, they build AI tools that can predict how molecules behave and help researchers design new drugs or materials much faster than before.
A grant that opens doors to new scientific possibilities
Receiving an ERC Consolidator Grant marks a significant milestone. For Simon Olsson, the award is both an honour and an opportunity.
“First, it is a great honour to be recognised by my senior peers in the field who reviewed the grant and served on the committee. It allows my group and myself to have focused time to pursue several ambitious research goals.”
About the ERC Consolidator Grant
The research grants from the European Research Council, ERC, are aimed at tackling major questions across all scientific disciplines. The Consolidator Grant is given to researchers with 7–12 years of experience since completion of PhD, a scientific track record showing great promise and an excellent research proposal.