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can personalize and automate home environments to improve comfort for residents, including temperature control, lighting, and air quality. Objective 3: Assess the role of digital twin technology in
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integration, and real-time optimisation, the project will ultimately help develop an adaptive system that helps pilots and controllers make smarter decisions mid-flight. The research will advance through three
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robotic automation to identify and optimise lead compounds. This approach will serve as a test case for a generalisable platform for rapid, structure-guided antiviral discovery. Approach and Methods
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automated feeders), and analyse microbiome composition using 16S rRNA and whole-genome sequencing. Statistical modelling will test for links between microbes and host development and fitness.� PROJECT
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engineering applications, and their tight integration with planning and control (e.g., task-and-motion planning, differentiable planning, or Reinforcement Learning (RL) with safety constraints). There will be
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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. This project aims to develop novel polymer-based nanoparticles for the non-viral delivery of mRNA vaccines directly to mucosal tissues, such as the respiratory tract. By leveraging high-throughput automated
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experimentation via laboratory automation and III) AI navigation of the complex landscape described. This powerful combination not only supports the creation of AMP based nanomedicines, but also addresses a central
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the risk of missed defects. Using the power of Artificial Intelligence (AI), this research aims to: - Automate defect detection in complex 3D structural data - Enhance diagnostic accuracy and processing
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About the ProjectProject details: Next-generation networks are rapidly outscaling the capabilities of traditional management paradigms. While early AI/ML models offered a degree of automation, they