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of thermodynamics, HVAC systems, or control systems is advantageous. Experience with environmental monitoring equipment, sensor systems, or energy modelling software will be beneficial. Effective communication skills
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vulnerable and mobility impaired individuals, and case study analyses. Proposals that use digital technologies in data capture are welcomed, for example GPS (location data) and other sensors that measure
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prevent failures. This project proposes developing a novel vision-guided robotic machining platform capable of adaptive manufacturing by integrating advanced sensors and AI. The work will involve
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advanced AI/ML methods to neural and behavioural data to uncover the computational foundations of decision-making in humans and animals. Designing novel AI algorithms inspired by brain function, to improve
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enabling precise and rapid identification of adulteration. Spectral techniques generate unique chemical fingerprints of food items, which machine learning algorithms analyse to detect inconsistencies and
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visual inspection. The research will address several challenges: Complex Surfaces: Developing robust algorithms (leveraging Convolutional Neural Networks and Transformers) capable of identifying tiny
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such as blockchain, IoT sensors, QR-based tracking, and integrated data platforms offer significant potential to enhance traceability, increase efficiency, and support sustainability objectives