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the groups of Dr Joe Forth, Dr Anthony Bradley, and Project Lead Professor Steve Rannard, applying your expertise in machine learning, cheminformatics, and soft materials to accelerate LAT design and
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asynchronous AI-led chemical optimisation across chemistry laboratories¿. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work
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. The project integrates synthetic organic chemistry, kinetic analysis, automation, and machine learning to establish next-generation mechanistic workflows for asymmetric organocatalysis. The project advances
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials