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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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managed to allow for efficient solar energy harvesting. This project will deliver novel methods for modelling and controlling LGS structural dynamics in the extreme orbital environment. The objectives
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focus on studying the effects of high energy propagation in poor weather and investigate methods for increasing energy transfer on an intended object. The project will allow you to acquire expertise in
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flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and mitigation system
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. The objectives will involve identifying and modelling different risks in the operational environments, including weather, communication, navigation, and ground risks, and developing autonomous decision making and
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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of artificial intelligence (AI) nowadays, it has become possible to develop a fast-response AI-based condition monitoring system for gas turbine engines. The objective of the project is to develop novel AI-based
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are expected to include: •Robust and “functionally explainable” machine-aided decision support for Safety and Mission Critical objectives e.g. fault detection/tracing, evasive manoeuvring, target selection etc
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problem. This project will develop a co-printing strategy to print a novel UAS body with novel properties to enhance defence and security applications. The main objectives are: Identify and evaluate
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lower orbit space debris). The increasing density of space objects in Lower Earth Orbit (LEO), including the proliferation of satellite constellations, further exacerbates the risk of collisions and the