Our mission is to enable machine learning algorithms to take a central role in all aspects of scientific discovery and to understand how such a transformation will impact the scientific approach as a whole. We identified four Research Areas in which progress is urgently needed to advance the use of machine learning in science and fully realize its potential to open new perspectives for science (1st funding period 2019 - 2025):
1. Beyond prediction, towards understanding (Research Area A)
2. Managing uncertainty (Research Area B)
3. Interface between algorithms and scientists (Research Area C)
4. Philosophy and ethics of machine learning in science (Research Area D)
In addressing these questions, the members of the cluster work closely together with the newly established Cluster Research Groups (Professors, Junior Research Groups, Ethics & Philosophy Lab), the scientists in our Innovation Fund Projects and members of our two Core Facilities (Machine Learning ⇌ Science Colaboratory and Machine Learning Science Cloud).
