Research areas
SMASH will form a close-knit community of postdoctoral scientists and their mentors, focused on a single unifying concept: using cutting-edge data science to answer some of the world’s most challenging questions. Through data science and massive computing power, SMASH wants to build intellectual bridges between studies of science and the humanities to encourage societal breakthroughs.
Research areas
1.1 Learning from complex data and computational scientific discovery
1.2 Deep learning and computer vision
1.3 Beyond supervised learning
1.4 Software and infrastructure for High-Performance Computing
2.1 Dark matter and gamma-ray astrophysics with the Cherenkov Telescope Array
2.2 Cosmology and time domain astrophysics with the Vera Rubin Observatory
2.3 New physics at the Large Hadron Collider
3.1 Linguistic knowledge injection into deep learning
3.2 Animal communication
3.3 Cross-lingual transfer for less-resourced languages
4.1 Extreme weather
4.2 Role of anthropogenic and natural aerosols and their complex mixtures on the climate
4.3 Determination of sources of air pollution
4.4 Machine learning based long-range atmospheric forecasting
5.1 Early detection and monitoring of diseases, including Parkinson’s disease and glioblastoma
5.2 Research in explainable AI in personalised medicine
5.3 Biomarker discovery