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Field
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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research on designing mobile energy hubs, energy systems integration, resilience analysis, and developing digital twin models and AI-enabled algorithms. You will conduct lab and field tests, analyse data
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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the development of Explainable AI Systems that can provide explanations of AI agent decisions to human users. Past work on plan explanations primarily focused on explaining the correctness and validity of plans. In
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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure
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collaborative research, further developing expertise within the field. Key Responsibilities Conduct research on complex quantum processes, particularly using the process tensor formalism, and leverage practical
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data on homeowner retrofit needs and preferences. Undertaking research trials to test and refine the AI algorithms used in our platform. Meaningful assistance in research and policy development with a
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and the role of key architecture components can lead to the development of more efficient and robust training algorithms. This can ultimately result in AI systems that are both more powerful and