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on expensive manual annotations. To improve cross-device and cross-task generalisation, enabling models trained on one dataset or device to adapt to others with minimal retraining. To improve detection and
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five‑year collaboration integrating materials growth, advanced microscopy and spectroscopy, nanoelectronic device fabrication, and machine‑learning‑accelerated modelling. As a member of my group, you
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representations Efficient AI deployment on edge devices Real-world AI systems for security, healthcare and smart environments The research will utilise anonymised industry datasets and be validated using
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, computer vision, federated learning, foundation models, adaptation techniques, multimodal learning, longitudinal image analysis or related areas, evidenced through coursework, research projects
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spectroscopy and Gaia data of star clusters to decipher the mystery of the Lithium-rich giant stars" (with Prof John Lattanzio) "The origin of the heavy elements: Computer simulations of neutron-capture
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grow new materials by molecular beam epitaxy, or create heterostructures of materials by exfoliating and stacking atomically thin layers from crystals, and fabricate nanoscale electronic devices
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, shape, composition that are responsive to light, heat and x-ray towards energy harvesting and storage, thermoelectric and optoelectronic devices. This scholarship application is open until filled. Student
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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nonlinear Hall effects in transition-metal kagome compounds. High-quality single crystals will be synthesised, fabricated into micro-devices, and studied via physical property measurements to probe quantum
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to integrate next generation satellite radar (InSAR) monitoring for ground motion with Global Navigation Satellite Systems (GNSS) positioning devices. This will focus on test sites where the student will