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well as retinal fundus images, we will explore analysis of new eye image datasets including OCTA and CCM images for diagnosis of diabetic neuropathy Machine Learning: We will develop artificial intelligence (AI
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sluggish diffusion kinetics of HEAs make them excellent candidates for resisting oxidation and corrosion in high-temperature steam. Guided by thermodynamic modelling and machine learning, we will identify
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these syndromes occur where and when they do? The student will develop statistical and machine learning models to (i) explain the occurrence of extreme fires and (ii) predict their likelihood under present and
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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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Subject area: Drug Discovery, Sustainability, Laboratory Automation, Microfluidics, Machine Learning Overview: This highly interdisciplinary 4-year funded PhD studentship will contribute to cutting
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with, cloud computing and virtualisation technologies Familiarity and hands-on experience with machine learning techniques desirable Desirable to have work experience (through internships or similar) in
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approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
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and other asset classes Financial econometrics and machine learning. Corporate finance and accounting Corporate governance and shareholder value Corporate finance, networks and insider trading Market
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of the workflow. While the majority of the project is computer based, there is a small lab-based component in order to generate cell samples to be able to acquire the NMR data. Once proof of concept has been
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framework that compares and blends complementary paradigms of physics informed machine learning (such as PINNs, ODIL)—to (i) super-resolve experimental data, (ii) infer unknown parameters such as the