Designing code for chemists
Automation is vital to reducing the amount of time researchers spend carrying out tedious repetitive tasks. Automating these tasks boosts efficiency and reduces mental burnout when working in computational chemistry, machine learning or cheminformatics.
Our group actively develops cheminformatic tools designed to automate workflows for computational chemists. Examples of such workflows include automatic end-to-end generation of output files from simple input, such as SMILES strings, and machine learning generation of results from raw datasets.