SPP 2363 on “Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning”

From Fundamentals to Application and Beyond
“Today the computer is just as important as tool for chemists as the test tube. Simulations are so realistic that they predict the outcome of traditional experiments.”
The Royal Swedish Academy of Science, 2013

SPP 2363 officially started

The DFG has selected suitable projects and the official funding letters were received. Let' get started, everyone!
Interested students, kindly contact the respective principal investigators.

“We must learn to understand chemistry as data science”

Frank Glorius and Philipp Pflüger talk about the new field of research “Molecular Machine Learning".

“Molecular Machine Learning” (MML) is a new branch of research with the potential to change chemical research. Prof. Frank Glorius, coordinator of the new Priority Programme “Molecular Machine Learning” (SPP 2363), funded by the German Research Foundation (DFG), and Philipp Pflüger, who is working on his PhD in Chemistry and helped to develop the programme, explain in this interview with Christina Hoppenbrock what MML means, what opportunities and challenges this new field of research presents, and what working in chemistry will be like in tomorrow’s world.

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