grad-training

This repository has training material for new graduate students on Georgia Tech's high-performance computing platform, PACE. The training material convers basics of Python and the Linux operating system, basic density functional theory (DFT) topics in Quantum Espresso and SPARC, and useful machine learning (ML) techniques. It also introduces the Atomic Simulation Environment (ASE) that can be used to build molecules, bulk crystals, slabs and nanoparticles and ASE calculators that are required to calculate energetics of chemical systems.

The training is not meant to be comprehensive. By the end of the training, you should be able to (i) use engineering intuition to assess the validity and meaning of DFT and ML data and (ii) understand papers and hold discussions about these topics with other group members.

This repository is split into 8 topics, each with its own folder containing resources, examples, and practice exercises. Each topic should take roughly 1 week.