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Administrative Data Research UK programme (ADR UK) . This studentship is one of a number attached to this programme and one of three linked projects addressing issues related to missing data. Early cancer
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access to amenities, active travel opportunities, and health-promoting environments. This project will empirically test both assumptions to develop a more nuanced, evidence-based framework linking chrono
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CFD predictions with quantum gas LiDAR measurements, using simulated and experimental data to relate observed concentration fields to underlying emission sources. This will include the development
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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collaboration with process engineers (Adrian Oehmen, Nasim Amiralian, both UQ) to determine adsorption capacity, regeneration efficiency, and long-term stability, generating the performance data required
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computer scientists to design paradigms that compare "active" learning (standard VR) against "proprioceptive" learning (haptically guided movement), measuring outcomes such as path efficiency, force
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, radiologists interpret scans such as CT, MRI, and X-ray together with textual information, including patient history, laboratory findings, and prior reports. Although recent Vision–Language Models (VLMs) can
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, computational modelling, or data science. The studentship provides full PhD funding, including tuition fees and a tax-free stipend for the duration of the programme. Please apply via the ‘Apply’ button above.
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of light. [1][2] This emerging technology holds enormous potential, offering routes towards new forms of highly parallelised information processing (optical computing), point-of-care diagnostics, next
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information and a detailed description of the research project, hit the 'APPLY' button above. Application Deadline: This PhD studentship offer will remain open until filled.