21 February 2024
Online webinar 16.00 – 17.00
The most recent wave of artificial intelligence (AI) in the form of Machine Learning (ML) has a great deal in common with techniques that chemists have used for many years. The difference lies in the scale of computation that is now possible. However, it also relies on the availability of significant amounts of quality data. I will discuss what AI/ML can offer the chemist and what chemists need to do (and know) to be able to make the best use of these techniques, to decide what we should be making and how we can make it (more) efficiently minimising energy and waste.
Jeremy is Professor of Physical Chemistry and Head of the Computational Systems Chemistry Group. He is an enthusiastic supporter of storytelling in interdisciplinary research, combining theory, computation and experiments addressing the wider digital economy. His experimental research uses lasers to probes of molecular organization from single molecules to liquid interfaces and biological systems with an x-ray microscope. In parallel he investigates how e-Science enables smart and intelligent laboratories; people, equipment and computers working smoothly together. This blends into his computational research on chemical informatics and the application of novel mathematical approaches, AI and Machine Learning, to chemical modelling.
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Tel: +44 (0)20 7598 1561