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performance of industrial systems (up to 100 MW+). You will receive specialist training through the Engineering Hydrogen Net Zero CDT and be based at Loughborough University. Primary supervisor Sonya Calnan is
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opportunity to interact with partners from the UK's Food Authenticity Network and to join a wider network of collaborators working to ensure the authenticity of natural products. During your PhD, you will
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PhD Studentship available in the EPSRC Centre for Doctoral Training in Robotics and AI for Net Zero (RAINZ) This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and
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PhD Studentship: Multi-robot Cyber-physical Systems for Solar Farm Health Monitoring and Maintenance
This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero Centre (RAINZ) which is a partnership between three of the UKs leading
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PhD Studentship available in the EPSRC Centre for Doctoral Training in Robotics and AI for Net Zero (RAINZ) This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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networking activities organized by the school. There are opportunities to interact with several UK and EU collaborators and travel to these labs for personal development opportunities. Supervisors:Professor
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-on experience in environmental management. Interdisciplinary training in hydrogeology, contaminant transport modeling, and decision-making. Networking & knowledge exchange with leading academic and industry
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cases. Additional engagement with other organisations may also be part of the research journey, providing exposure to a broad network of practitioners and stakeholders. Funding and Eligibility Fully
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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