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Field
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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reliability and maintenance strategies. Filter Rig: An experimental setup to study filter clogging phenomena, allowing for the collection of data to develop and validate prognostic models for filter
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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(e.g., in the context of risk, uncertainty, future thinking), social processes (e.g., interpersonal dynamics, social norms, and influence), and behavioral outcomes (e.g., behavior change, social action
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drives tumour development, childhood cancers lack the extended time frame needed to accumulate the mutations required for tumorigenesis by those routes. Therefore, endogenous mutagenic processes are a
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, which are essential for safe operation in these challenging aerospace environments. You will develop robust, physics-based models to analyse failure, with a focus on understanding mechanical and
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for healthcare. A2 Project or subject specific skills; e.g. experience of data collection, the use of AI/ML tools for processing collected data and understanding of hardware technologies to configure systems and
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processes. Objective 2: Develop methods to measure and assess interoperability, helping identify where and why issues arise. Objective 3: Create solutions that address interoperability challenges and meet
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-frequency Joule losses. Litz wire is one of the most promising solutions due to its exceptional ability to reduce AC losses and boost power density. Today's modelling tools are not yet equipped to fully