In an era dominated by technological advancements, the relevance of digital chemistry and automation cannot be overstated. Together, digital chemistry and automation enable researchers to explore and understand complex science more efficiently than ever before. Our course emphasises the pivotal role of automation and data-driven approaches in the future of industrial chemical research, effectively preparing our graduates for careers across a wide range of sectors such as pharmaceuticals, materials and chemical technology.
You will learn how to collect, analyse and exploit large chemical datasets, and how these can be integrated with your chemical knowledge and machine learning approaches to solve real-world challenges. This dual focus on data generation and handling will provide you with the skills required to fully harness the potential of digital chemistry, both computationally and applied in a laboratory setting.
At Leeds, you will be immersed in an active digital and automated chemistry research environment. You will have the opportunity to carry out an original independent research project which aligns with your interests and career aspirations, ranging from the discovery of new drugs, materials and catalysts to the development of efficient and sustainable manufacturing processes, including predictive chemistry.
During the Digital and Automated Chemistry MSc course, you will learn how to seamlessly integrate chemistry and advanced technologies, providing you with the knowledge and skills needed for a career within the modern chemical sciences industries. You will also have the opportunity to develop a range of additional key skills throughout the course, including problem solving, critical thinking, project planning and scientific communication.
[Learning Outcomes, Transferable (Key) Skills, Assessment]
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Candidates will be required to study the following compulsory modules
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| CHEM5900M | Enabling Technologies in Chemistry | 15 | Semester 1 (Sep to Jan) | PFP |
| CHEM5910M | Data Science for Digital Chemistry | 15 | Semester 1 (Sep to Jan) | PFP |
| CHEM5920M | Machine Learning for Autonomous Chemical Process Development | 15 | Semester 2 (Jan to Jun) | PFP |
| NATS5500M | MSc Research Project | 60 | 1 Jan to 30 Sep | PFP |
| NATS5700M | Advanced Practical, Professional and Research Skills for Scientists | 30 | Semesters 1 & 2 (Sep to Jun) | PFP |
Candidates will be required to study 45 credits from the following optional modules:
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| BMSC5231M | Structure-based Drug Discovery | 15 | Semester 2 (Jan to Jun) | |
| CHEM5012M | Foundations of Chemistry - Coursework | 15 | Semesters 1 & 2 (Sep to Jun) | |
| CHEM5107M | Modern Drug Discovery | 15 | Semester 1 (Sep to Jan) | |
| CHEM5617M | Advanced Topics in Chemistry (Coursework) | 30 | Semesters 1 & 2 (Sep to Jun) | |
| CHEM5618M | Advanced Topics in Chemistry (Examined S1) | 15 | Semester 1 (Sep to Jan) | |
| CHEM5619M | Advanced Topics in Chemistry (Examined S2) | 15 | Semester 2 (Jan to Jun) | |
| CHEM5800M | Introduction to Sustainability Science and Technology | 15 | Semester 1 (Sep to Jan) | |
| CHEM5810M | Renewable Materials for a Sustainable Future | 15 | Semester 2 (Jan to Jun) | |
| CHEM5820M | Green Chemistry and Sustainable Processes | 15 | Semester 2 (Jan to Jun) |
** For students without a degree in Chemistry, CHEM5012M will be compulsory in Semester 1.
[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable
Last updated: 29/04/2025 17:02:45
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