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(CHF), tailored to complex geometries typical of fusion reactor cooling systems. Compile a comprehensive dataset of boiling parameters to support machine learning-based analysis of two-phase flow
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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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/PYTHON/R/C programming • Application of Machine Learning Algorithms Additional Information Benefits This scholarship covers the full cost of tuition fees, an annual stipend at UKRI rate (currently
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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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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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implement more effective interventions based on up-to-date predictions. The ideal candidate will have foundational knowledge of machine learning and strong self-motivation. You will be supervised by Dr
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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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