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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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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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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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, 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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latitudes. Student profile: The project requires the student to be relatively proficient in Python programming to use and modify existing software, as well as for potentially developing new diagnostics and
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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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, 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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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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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
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models. This framework should be engineered to simulate a range of attack scenarios with high fidelity (i.e. exploitation of network and device vulnerabilities). Abertay University possesses a mature, well