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Field
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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technologies used in and connected to grids (e.g., distributed generation, storage, electric vehicles, heat pumps, smart energy management systems, etc.) and how to design grid tariffs that align grid and market
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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architectures and distributed storage integration. Examining the physical arrangement, fire safety, redundancy, and maintenance requirements for embedded storage. Evaluating economic considerations, including
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programme is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete research training to the level of a
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Project advert Madagascar is a globally important biodiversity hotspot, home to hundreds of endemic species. At juxtaposition with this rich natural heritage is a growing human population and a
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors
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Location: Students will be based at the CREWW building on Streatham Campus in Exeter. Flooding is the most common natural disaster, impacting billions worldwide. Natural Flood Management (NFM), a