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: The occurrence and distribution of species within and around solar parks, identifying key “winners and losers” in terms of biodiversity. How species interactions, including plant-pollinator networks
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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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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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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience
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). The FIBE3 CDT aims to lead a transformation to net zero infrastructure through industry partner co-creation and co-delivery of an inspirational doctoral training programme for cohorts of emerging talents from
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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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. 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, continuous development
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, intake design, and computational methods. The research will directly support the Net Zero ambitions and contribute to the UK’s strategy of global competitiveness in aero-engine technologies. It will also
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access to state-of-the-art facilities and a network of professionals in the field. The expected impact of this research will be the development of valuable insights into how advanced technologies can be
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part of the EPSRC Centre for Doctoral Training (CDT) in Net Zero Aviation, offering an integrated, multidisciplinary training programme focused on innovation, collaboration, and inclusive leadership. As