The High-Throughput Toolkit (httk) is a toolkit for preparing and running calculations, analyzing the results, and storing the results and outcome in a global and/or in a personalized database.

Search the Eropass job postings for given keywords

Phonon code

SchNetPack - Deep Neural Networks for Atomistic Systems

Universal material graph interatomic potential with three-body interactions

The Wren sits on its Roost in the Aviary.

Keras layers for end-to-end learning on molecular structure.

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

A code to generate atomic structure with symmetry

Graph neural network for predicting energy of known and hypothetical crystal structures

Hands-on exercise 2 documentation repository

yaspi - Yet Another Slurm Python Interface

repository and website for tutorials on 3d Euclidean equivariant neural networks

Symmetry prediction and knowledge discovery fromX-ray diffraction patterns using an interpretable machine learning approach

Atomic interaction potentials based on artificial neural networks

A toolkit for querying data in OQMD.

Atomic Simulation Environment - unofficial mirror from https://gitlab.com/ase/ase

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It i…

Materials Interface: methods in computational materials science