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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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three coupled components. First, a physics-informed graph surrogate model will emulate network hydraulics at scale, representing pipes and assets as a graph and predicting flows, depths, surcharge
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of light. [1][2] This emerging technology holds enormous potential, offering routes towards new forms of highly parallelised information processing (optical computing), point-of-care diagnostics, next
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, etc.), or the equivalent qualifications gained outside the UK, in a relevant area of Physical Science, Materials Science, or Engineering. You should be able to demonstrate some computational