Computational chemist, MSc in Molecular and Biological Chemistry at EPFL. I work where molecular simulation meets machine learning.
What I've worked on
- Screening 108 Cu-based alloy catalysts with equivariant ML interatomic potentials instead of DFT
- Comparing free-energy methods (MM/PB(GB)SA, thermodynamic integration, funnel metadynamics) for PFAS binding to a protein, on the CSCS Alps GPU supercomputer
- Interpretable symbolic-regression models of spin states in iron complexes
- Contrastive models that retrieve molecular structures from NMR, IR and MS spectra (EPFL AI Team, ongoing)
Tools: Python, PyTorch, RDKit, GROMACS, PLUMED, Gaussian, Psi4, SLURM/HPC
Looking for: a master's thesis in AI for chemistry or materials, from February 2027. LinkedIn · CV · cedric.rossboth@epfl.ch