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Field
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challenge, making energy-efficient computing a critical research priority. This project addresses this challenge through a novel co-design approach that simultaneously optimizes both hardware and software
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Engineering, and Engineering Management. Students with interests in computational mechanics, optimization design, bioinspired design, sustainability management, machine learning, AI, uncertainty quantification
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(technical personnel and toilet users), implementing AI-driven data analytics for system optimization, and creating predictive models for environmental and social impact assessment. Students will work with
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changes in the overall national supply chain structures to resilience, and suggest interventions, together with those informed via stakeholder consultation in WP1, for finding optimal solutions to mitigate
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pursuing excellence in research and education, we also aim to optimize our positive impact on society—examples include collaborations with industry partners and charities, commercialisation activities and an
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environmental inputs, algae physiological parameters and microbial community eDNA data to develop predictive mechanistic models which can be utilised to develop an optimal cultivation strategy. The project is
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systems. This project aims to understand how cells in the central nervous system efficiently fill space during development -a process critical for optimizing functions like sensory information processing
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still hampered by: Ability to detect areas along the intertidal for optimal restoration3. Knowledge on how positive species interactions can be harnessed for rapid restoration4. Availability of devices
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Accountabilities Design and implement software pipelines to deploy ML models on edge devices with real-time inference capabilities. Optimize machine learning models (e.g., quantization, pruning) for edge hardware
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component of large Wellcome Trust project, ‘Optimal implementation of Wolbachia wAlbB programmes for dengue control’. They will have a strong background and experience in economic evaluation, especially in