Machine Learning in Science MSc

The development and use of machine learning (ML) and artificial intelligence (AI) have revolutionised areas such as computer vision, speech recognition and language processing.<br/><br/>On this course you will learn how to apply ML and AI techniques to real scientific problems. This will help you build vital skills, enhancing your employability in a rapidly expanding area.<br/><br/>Graduates of this course will learn how to:<br/><br/>identify and use relevant computational tools and programming techniques<br/>apply statistical and physical principles to break down algorithms, and explain how they work<br/>design strategies for applying machine learning to the analysis of scientific data sets.<br/>In addition, you will develop a broad set of transferable skills, including communication, critical thinking, and problem-solving. Previous students of this course have undertaken paid part-time internships with external partners.<br/><br/>Find out what our graduates say about the course on our Physics Blog.<br/><br/>You will have the opportunity to develop your own research project on a topic of your choice. Previous projects have looked at:<br/><br/>Deep Learning for drug discovery<br/>Machine Learning for sustainable solvent selection<br/>Quantum reinforcement learning<br/>Supervised machine learning on a quantum computer<br/>Deep Learning network for fatigue monitoring of wind turbine blades<br/>Shaking all over – vibration cancellation at the atomic level<br/>Using machine learning to automatically segment the placenta from pregnancy MRI scans<br/>Machine learning assisted high-throughput computational screening of metal organic frameworks for biogas upgrading<br/>Simulating the Universe<br/>Detecting dark matter substructure in galaxies<br/>Personalised modelling of cerebral blood flow from multi-modal features for early detection of dementia<br/>Machine Learning natural product biosynthesis<br/>Advanced natural language processing in Fintech