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networks by analyzing their dynamical systems and probabilistic asymptotic behavior, improving and generalizing diffusion-based generative AI using insights from numerical and stochastic analysis, and making
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opportunities for building important research skills and networks among your peers and research academics Entry requirements: Applicants should have, or expect to achieve, a first-class or upper-second-class
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research skills and networks among your peers and research academics. Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in a chemistry related
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existing experience. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning
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education, research, and innovation, which has been inspiring generations of thinkers for over 400 years. The disaggregation of Radio Access Networks (RANs) introduces new challenges in energy management
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can be used to produce high value molecules from lignin rich wastewaters that arise from the paper industry. Motivation This project will form part of a wider network of European partners spread across
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions
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the CDT in Net Zero Aviation, which offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement
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Applications are invited for a Research Assistant to join the Integrated Clinical-Computational Affective Research Unit (ICARUS). The unit is led by Dr Liam Mason (Associate Professor of Clinical