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Hello! 👋

I'm Marcel, a postdoc in the COSMO Lab at EPFL in Lausanne, Switzerland. Previously, I was a doctoral student at the Fritz Haber Institute (in the NOMAD Laboratory) and TU Berlin (in the Machine Learning group).

I work on applying machine learning to materials science problems. Recently, I've particularly focused on machine-learning potentials and the computation of thermal conductivities with the Green-Kubo method. To this end, I've written the glp and gkx packages, both using jax.

Here are some other places on the internet you can have a look at:

Thanks for stopping by 🚀

Marcel's Projects

cmlkit icon cmlkit

tools for machine learning in condensed matter physics and quantum chemistry

cscribe icon cscribe

cmlkit plugin for the dscribe package

floq icon floq

FLOQ - A Python module for smooth robust quantum control

gknet-archive icon gknet-archive

data and code for "heat flux for semi-local machine-learning potentials"

gkx icon gkx

Green-Kubo + JAX + MLPs = Anharmonic Thermal Conductivities Done Fast

glp icon glp

tools for graph-based machine-learning potentials in jax

glp-archive icon glp-archive

data and code for "stress and heat flux via automatic differentiation"

home icon home

A very rudimentary home page in php adapted from Shaun Inman's unplayed

i-pi icon i-pi

i-PI: a universal force engine

miniphonic icon miniphonic

A paper-thin Ruby wrapper around the auphonic.com API

mlff icon mlff

Build neural networks for machine learning force fields with JAX

nequip icon nequip

NequIP is a code for building E(3)-equivariant interatomic potentials

octolog icon octolog

the octopress setup powering lumenlog.com

schnax icon schnax

An implementation of SchNet in JAX and JAX-MD.

schnetpack icon schnetpack

SchNetPack - Deep Neural Networks for Atomistic Systems

son icon son

sequential object notation

specable icon specable

[draft] dictionaries to objects and vice versa

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