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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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to achieve, at least a 2.1 honours degree or a master’s in a relevant science or engineering related discipline. Applicants should have strong background in Machine Learning and Deep Learning. To apply, please
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interdisciplinary team working on the development of cross-platform alignment technologies that integrate material science, process engineering and sustainability analysis to deliver scalable solutions for circular
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Department/Location: Department of Engineering, Central Cambridge We are seeking a highly motivated Research Assistant/Associate to join EPSRC and industry funded Digital Roads (DR) Prosperity
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DEPARTMENT OF HEALTH TECHNOLOGY AND INFORMATICS Research Assistant Professor in Medical Laboratory Science / Biomedical Science / Medical Imaging and Radiation Science / Medical Physics / Medical
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the recording of substrate-borne vibrations produced by earthworms (and other invertebrates) in situ. To fully exploit this emerging technology there is a need to unravel the meaning within the data. As such
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project will involve collecting and analysing EEG, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab
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Portal: applyto.newcastle.ac.uk In ‘Course choice’ tab, put ‘Postgraduate Research’ in 'Type of Study', ‘Full Time’ in ‘Mode of Study’, ‘2025’ in ‘Year of Entry’, code ‘8440F’ in ‘Course Title’, blank in
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, fNIRS and home wearable recordings from babies and children. Experience of advanced data analytics, including if possible experience of coding in Matlab and/or Python, is highly desirable. Experience
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physiology etc. This PhD project is suitable for applicants with a background in Electrical and Electronic Engineering or closely related fields. Candidates with a strong interest in RF engineering and/or