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mechanisms, with the current generation having significant drawbacks, including low energy efficiency, high operating voltage or temperature. This project will develop the materials, methods, and designs
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training in computational tools and statistical methods over the course of the project. The project includes placements at NPL and Waters-TA Instruments, with opportunities to work in state-of-the-art
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Jaguar Land Rover and WMG (University of Warwick). The collaboration seeks to investigate and develop new joining methods of battery pack module assemblies. The biggest challenge is moving away from
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from other acquired brain injuries (e.g., traumatic brain injury, brain tumour, stroke) – this work package will include quantitative and qualitative studies; second, to develop a training programme for
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such as transportation and heating. These two transformations create a need for sophisticated planning methods and processes that result in actionable plans by proactively considering high-impact forces
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State University of New York University at Albany | Albany, New York | United States | about 19 hours ago
Administration and Policy and (2) Faculty Affiliate with the Information Science Ph.D. Program. Primary Responsibilities: Preparation of research proposals Literature reviews Empirical fieldwork (collection
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will develop and apply cutting-edge methods in predictive and causal modeling for age-related macular degeneration (AMD), a primary cause of irreversible vision loss worldwide. This work will involve
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complemented with mesoscale experiments involving connected patches of woodland communities to assess their reaction to change. Data from both experiments and the field will be used to inform computational
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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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delivery or regenerative medicine. The student will formulate new 3D-printable materials and develop new design methods, for functional 4D-printed devices with either fast self-resetting responses or complex