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biology approaches to identify transcriptional networks and signalling pathways controlling cardiovascular development. Using novel datasets generated from mouse models of congenital heart defects, the
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Polymer manufacturing is highly energy intensive, and achieving net zero requires more than fuel switching. This project focuses on process systems engineering for industrial decarbonisation
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-generation power electronics in the form of Solid-State Transformers which will provide key functionality in the electricity networks of the future which will feed, for example, high power charging systems and
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unique opportunity to gain expertise that is highly sought after across pharmaceutical and advanced manufacturing industries. This project is part of the EPSRC CDT in Process Industries: Net Zero . The
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basis therefore we encourage early expression of interest. Net2 Zero Centre for Doctoral Training The EPSRC and BBSRC Centre for Doctoral Training in Negative Emission Technologies for Net Zero (CDT in
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within water distribution systems. The research will investigate how network connectivity, sensor information, smart-meter data, operational conditions, and information from neighbouring areas can be
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’–mechanical networks built from many sensors and actuators that locally communicate with one another to achieve collective functionality. These active networks could enable next-generation bioinspired robots
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per year, subject to annual increases. About the Project (Background & Methodology) Autonomous systems such as drone fleets, mobile robots, and sensor networks increasingly use federated learning (FL
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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be an integral member of the wearables group based at Oxford, led by Aiden Doherty. Our research team has access to world-leading population health data sets with objective wearable sensor measurements