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but opportunity to attend conferences and to link with industrial experts in the field. The applicant is envisioned to further enhance and develop world class skills in AI and Machine Learning with
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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate
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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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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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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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) 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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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
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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