The CAMLC workshop

The "Cheminformatics, Automation and Machine Learning in Chemistry: from fundamental concepts to emerging techniques" (or CAMLC for short) workshop aims to introduce attendees to the use and development of emerging digital technologies in chemistry. Initially, attendees will review various functions of Python, particularly those related to modules commonly used in cheminformatics. Once users are familiar with Python environments and Jupyter Notebooks, machine learning and data science will be introduced, with a focus on state-of-the-art implementations in the field of chemistry. It is particularly relevant for computational and experimental chemists who work with the following:

Fields

  • Chemical machine learning or cheminformatics
  • Computational chemistry
  • Organic or inorganic chemistry

Research topics

  • Homogeneous or finite systems
  • Machine learning modeling and predictions
  • Automation of quantum mechanics and machine learning workflows
  • Catalyst and ligand design
  • High-throughput experimentation
  • Drug discovery


Requirements

  • Good command of English (language of the workshop)
  • Participants must bring their own laptops to follow the workshop
  • Sessions are in-person only


  • Basic level of Python or other computing languages
  • Basic level of computational chemistry (or familiarity with DFT calculations)