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-structure noise and rapid regime shifts. Integrate real-time data streams. You will experiment with heterogeneous inputs like tick-level prices, news sentiment, order-book depth, macro indicators and
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-engaged and participatory research approaches are particularly welcome, and the successful candidate will be supported with access to local networks, data, and industry expertise. Benefits
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Vulnerability Detection of Smart Grids with a Specific Focus on Generative Adversarial Networks (GAN) Attacks Primary supervisors: Professor Damminda Alahakoon & Dr Shalinka Jayatilleke Other supervisors
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for this project. The successful applicant will be required to hold a Working With Children Check (WWCC) and police check, at their own cost, in order to undertake field work and to be onboarded with FNLRS data