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with fabrication engineers to translate physical processes into machine learning models, design and train deep learning architectures, and evaluate their ability to generalise across different process
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, spectroscopy, and electrical performance measurements. You will work closely with fabrication engineers to translate physical processes into machine learning models, design and train deep learning architectures
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. Deliver high-quality measurements of plant physiology and growth under defined environmental and acoustic conditions. Lead below-ground sampling and analyses, including root phenotyping/architecture
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, including root phenotyping/architecture assessment and root evaluation. Undertake rhizosphere-related measurements including root exudates and the collection and analysis of the root microbiome Set up
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the neural-network control of a tiled array of fibre lasers in a coherent beam combination architecture, for unlocking novel scaling and beam shaping capabilities in real-time. You will work at the
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laser’, through the neural-network control of a tiled array of fibre lasers in a coherent beam combination architecture, for unlocking novel scaling and beam shaping capabilities in real-time. You will
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findings at international conferences. Required qualifications and experience: To succeed, you will hold a PhD (or be close to completion) in Computer Science, Applied Mathematics/Statistics, Physics