MSc AI and Digital Chemistry
Why Study this Course?
AI applications - learn how to use AI methods and computational approaches to solve chemical problems
Future-proof skills - become literate in data science and AI
Graduate industry-ready - we'll teach you the skills to enable you to be problem solvers and innovators
Module choice - study a wide range of chemical principles and specialist topics
Industry exposure - opportunity to be supervised with industrial collaboration on your research project
Industry Impact - content informed by experts in the chemicals industry
Learn more about the MSc in AI and Digital Chemistry from course director Prof. Jonathan Hirst
Visit our online prospectus
Course Overview
Example modules for the MSc AI and Digital Chemistry
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Module
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Credits
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Description
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Machine Learning in Science Part I
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20
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Introduces the main concepts and methods of machine learning.
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Machine Learning in Science Part II
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20
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Covers advanced machine learning, including modern deep learning methods and applications.
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Advanced Quantum Chemistry
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20
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Introduces quantum mechanical approaches to perform simulations of chemical systems using a range of techniques.
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AI for Drug Design
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20
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Focuses on the application of AI to drug discovery, exemplifying how those approaches can provide an understanding of medicinal chemistry.
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Molecular and Materials Modelling
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20
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Presents computational chemistry methods as applied in the discovery, development and design of materials and molecules.
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AI and Digital Chemistry Project
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60
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A summer research project on the application of the AI and computational techniques to a chemical problem and covering general skills for project work, AI & digital research methods, AI and research ethics, research integrity, literature survey, data management and data analytics.
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Research Projects
You will have the opportunity to develop your own research project on a topic of your choice.
Indicative projects include:
- Deep learning for drug discovery
- Machine learning for sustainable solvent selection
- Machine learning assisted high-throughput computational screening of metal organic frameworks for biogas upgrading
What our Industrial Partners Say
“The course topics fit with many of the requirements we are looking for in industry.”
Vice-President, Chemistry, Croda
“Being able to look at a list of molecules and identifying potential issues e.g., complexity, solubility, trends in acidity. These are hugely beneficial and would help a candidate stand out amongst other machine learning backgrounds.”
Senior Scientist, Sygnature
Applying
To learn more about how to apply for the MSc in AI and Digital Chemistry click on the links below. If you have further questions please contact chem.admissions@nottingham.ac.uk