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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
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Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
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variants of importance sampling. We will connect these methods to modern formulations of Monte Carlo algorithms to improve their accuracy, scalability, and overall computational cost. The methodology so
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et al (2015). A hybrid metaheuristic algorithm for the multi-depot covering tour vehicle routing problem. European Journal of Operational Research.
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of