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Field
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comprehensive analysis of the extensive Pulse dataset, uncovering latent patterns and taxonomies that define building leakage characteristics. Surrogate Model Development: You will develop data-driven surrogate
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to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom. Entry requirements Applicants should have a first or
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: The occurrence and distribution of species within and around solar parks, identifying key “winners and losers” in terms of biodiversity. How species interactions, including plant-pollinator networks
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that define building leakage characteristics. Surrogate Model Development: You will develop data-driven surrogate models capable of estimating air leakage in unseen building types. These models will be trained
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contribution will have a lasting impact. As a member of our vibrant community of 22,000 students and 8,000 staff, you will collaborate with passionate minds across nine London campuses and a global network. This
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attend international and national conferences to present your work and network with other scientists from across the globe. At the end of your PhD, you will be an accomplished and highly-capable scientist
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, management, quantitative analysis Lead in publication outputs in appropriate academic and industry fora The role-holder will also have management, liaison and networking responsibilities. The skills
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, management, quantitative analysis Lead in publication outputs in appropriate academic and industry fora. The role-holder will also have management, liaison and networking responsibilities. The skills
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will then embark on coming up with a suitable design for a generic economic model and construct the model using their software of choice. This new generic model can then be demonstrated by using data
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into full-surface temperature profiles. Key outcomes include defining the required locations and extent of temperature monitoring to enable accurate data conversion. • Creating a practically deployable method