250 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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learning and machine learning for biological data Sequence and structure analysis of large-scale datasets Functional annotation and evolutionary analysis Collaborative research with experimental virology
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Understanding plankton biodiversity and ecosystem change by applying machine learning – A CASE studentship Lead Supervisor (DoS): Professor Abigail McQuatters-Gollop Second Supervisor: Dr Clare
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environments: The C-Wild Warrington lab (Ecology and Conservation ) and the Machine Learning and Robotics research group (Artificial Intelligence, Data Analysis and Systems ). This will provide
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aspects of machine learning. Applications include improving the efficiency of data assimilation methods and understanding why and how deep learning works. Applicants should have, or expect to achieve
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Bachelors Honours degree (or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject Area Medical imaging, biomedical
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failures before they occur, enabling proactive maintenance strategies. Anomaly Detection Mechanisms: Implement machine learning techniques to identify and classify anomalies in electronic systems, enhancing
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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, and explainable machine learning to analyse campaign text, imagery, and investment outcomes. While experience in analytics or programming is desirable, training and supervision will be provided
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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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