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Field
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of offshore wind is essential for developing effective mitigation strategies and adaptive management efforts. Methodology Wind turbines often face opposition from residents due to their space requirements, as
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distribution of economic benefits among marine stakeholders and opinion-holders (Willis-Norton et al., 2024). Understanding these dynamics is critical for informing policy decisions that mitigate negative
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We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only
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topological context and data access patterns. A successful candidate will work in the Distributed Systems and Concurrency group at University of Surrey and benefit from close collaboration with Neo4j, a world
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interactions/contacts. Monitoring and analysing contact pressure, surface contact distribution, and friction and movement patterns for personalised adjustments to equipment (and training). Based in both
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No of positions: 1 The scholarship is funded by the New Lecturer Scholarship scheme (available to home students only). Currently, no scholarships are available for international students. However
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, particularly in computer networks, operating systems, computer architecture and distributed systems Excellent programming, system building and measurement skills are required Be familiar with, and ideally worked
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critical to act on those hotspots for energy demand and/or GHG emissions. One of these potential areas of action is the food cold chain – the manufacture and distribution of frozen, refrigerated and chilled
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used in producing fine chemicals, including pharmaceuticals. By leveraging state-of-the-art advances in computer vision and machine learning, we aim to manipulate Particle Size and Shape Distribution
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Self-funded PhD opportunity in 6G as part of major project hub, further funding possible subject to progress of project and student. Focus on native AI in 6G systems with experimental testbed and