MSc AI and Digital Chemistry

Program Overview:
The MSc AI and Digital Chemistry at the University of Nottingham combines chemistry with machine learning, data science and computational modelling to prepare students for modern, digitally driven chemical research. It suits graduates in chemistry or related fields who want to apply AI to drug discovery, materials design or sustainable chemical innovation.

Curriculum Structure:
Students begin with Machine Learning in Science – Part I, learning core methods such as regression, classification and clustering as applied to chemical datasets. They then progress to Machine Learning in Science – Part II, where they study deep learning, neural networks and data-intensive modelling tailored to molecular and materials science. Optional modules such as Advanced Quantum Calculations, Molecular and Materials Modelling, or AI for Drug Design allow them to work with quantum-chemical simulations, atomistic modelling and AI-driven design tools. The programme concludes with the AI and Digital Chemistry Project, where students carry out a substantial research investigation applying AI to a real chemical or molecular problem.

Focus areas: “Machine Learning for Chemistry, Computational Chemistry, Quantum Chemistry, Materials and Drug Discovery, Data-Driven Chemical Research”

Learning outcomes: “Apply ML and deep learning to chemical data; run computational chemistry and modelling tools; use AI for molecular and materials design; conduct independent AI-driven chemical research.”

Professional alignment (accreditation): Designed to meet industry and research needs in pharmaceuticals, materials science, green chemistry and computational chemistry.

Reputation (employability rankings): Nottingham’s strong standing in chemistry and research enhances graduate prospects across chemical, pharmaceutical, materials and data-driven science sectors.