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Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy" How to apply: https://uom.link/pgr-apply-2425 How many positions: 1 This 3.5 year PhD is open to UK
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skills will be provided. Preferred candidates will have a PhD (or equivalent experience) in computer science, machine learning/AI, sustainability, or other related subject. A strong interest in the
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat
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in computer vision and intelligent transportation. Experience with tools such as MATLAB, Python or machine learning frameworks is highly desirable. Supervisor: Dr Ning Zhao (N.Zhao@bham.ac.uk
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and has a large group of collaborators. You will be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn More: The Dynamics Research Group
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overseas. Training can be provided in computational fluid dynamics, machine learning, and nonlinear dynamics. These skills are highly valued across a wide range of industries. Recent data reveals that Fluid
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) Familiarity with machine learning models, for example, large language model (Desirable) *This opportunity will cover UK/Home fees. Overseas students who wish to apply would need to be able to finance
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be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn more: The Dynamics Research Group: drg.ac.uk Digital Twinning Interest Group
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main project by addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods
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this overall aim, the student will Employ computer programming methods to determine the occurrence of Alzheimer disease in obstructive sleep apnoea patients using previously collected clinical data and Perform