COURSE CURRICULUM

The Digital and Automated Chemistry MSc combines core training in practical, computational and research skills with opportunities to specialise in advanced chemical topics. Compulsory modules provide a strong foundation, beginning with Advanced Practical, Professional and Research Skills, which develops hands-on expertise in digital chemistry, laboratory techniques and transferable professional abilities. Data Science for Digital Chemistry introduces Python programming, data handling, visualisation and analysis of real chemical datasets, while Machine Learning for Autonomous Chemical Process Development focuses on process optimisation, design of experiments and the application of machine learning to improve efficiency and sustainability in chemical processes. The 60-credit Research Project forms the heart of the program, allowing students to undertake independent, original research using computational tools, algorithms and advanced laboratory techniques, supported by Leeds’ state-of-the-art facilities. Optional modules allow further specialisation in areas such as foundations of chemistry, modern drug discovery, structure-based drug design, sustainability science and green chemistry, as well as advanced topics in chemistry that reflect current research and industrial applications. Other options explore renewable materials, sustainable processes and multidisciplinary problem-solving. Together, the curriculum equips students with a blend of practical, computational, analytical and research skills, preparing them to apply digital and automated approaches to chemical challenges, including drug discovery, materials innovation and sustainable process development, and to pursue careers in both industry and academia.