To investigate the enhancement of traditional HPC simulations, SURFsara selected four scientific use cases spanning very different scientific domains. Prof. Alexandre Bonvin decided to work with SURFsara as they bring domain-specific expertise in choosing the right AI tools and approach along with the ability to help specify and train the proper neural network to assist their research using PDB (Protein Data Bank) data.
Grants like this are most welcome to develop our knowledge for deep learning purposes as well as to optimise future usage of our UBC HPC (GPGPUs) facility
The four selected use cases which SURFsara will work on are:
- Distinguishing biological interfaces from crystal artifacts in biomolecular complexes using deep learning – Prof. Alexandre M.J.J. Bonvin, Computational Structural Biology, Utrecht University;
- Machine-Learned turbulence in next-generation weather models – Dr. Chiel van Heerwaarden, Meteorology and Air Quality Group, Wageningen University;
- Machine learning for accelerating planetary dynamics in stellar clusters – Prof. Simon Portegies Zwart, Computational Astrophysics, Leiden University.
- Generating physics events without an event generator – Dr. Sacha Caron, Experimental High Energy Physics, Radboud University.