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Field
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methods for defect detection; Apply AI and machine learning techniques to process, analyze, and interpret complex NDE data; Create AI models for automated defect detection, classification, and
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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Join our dynamic, multidisciplinary team as a Research Associate and make a transformative impact in scientific machine learning and digital twins for healthcare innovation! This role focuses
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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. This project will develop responsive manufacturing technology that will have sufficient flexibility to overcome such problems by utilizing intelligent machine learning to control the printing process in real
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Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research Associate: A PhD (or
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considered. Qualifications/Skills PhD degree in a programme relevant to human-computer interaction and/or critical computing, ideally in Computer Science, Industrial Engineering, Interaction Design, or a
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Associate: A PhD (or equivalent) in an area pertinent to the subject area, i.e. Computer Science, Machine Learning, Robotics. Research Assistant: A Master’s degree (or equivalent) in an area pertinent
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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