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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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the support of leading biomedical researchers with strong ties to radiology, your work holds the promise of making significant impacts on patient care and advancing the field of cardiac health. What is offered
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. Ultimately, this work bridges the gap between the theory of advanced material science and the challenges of implementation in an industrial environment. This research contributes to advance the fundamental
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components with applications in the transport, catalysis and bioengineering industries. The research will focus on wet chemical processes and the study of chemical reactions on the component's surface. We will
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Department/Location: Department of Engineering, Central Cambridge A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations of MILD combustion. The post holder will be located in Central
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be based between the Faculty of Science and Engineering will conduct research into the latest gallium oxide power electronic devices. The research work will be undertaken in a state of the art, brand
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on Novel Materials for Stratospheric Aerosol Injection (Dispersal). The post holder will be located in
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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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We are seeking a motivated and detail-oriented Research Assistant to support ongoing research activities within our team. The successful candidate will work under the guidance and mentorship