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Field
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degree in Electrical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field, with a genuine interest in Wearable Technology, Sensor Development, Biomedical Devices, and Data
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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are looking for: A PhD (or have submitted your thesis before taking up the role) in Materials, Physics, Chemistry or a closely allied discipline Expertise in 4D-STEM data acquisition Expertise in cryogenic
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repeated global LiDAR measurements related to biomass. Sentinel missions offer increased temporal resolution in both multispectral (for vegetation indices) and SAR data (for moisture and structure
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, Continuum Mechanics, Computer Science, Materials Science, Physics or a related subject, or relevant industrial experience. English language requirements: Applicants must meet the minimum English language
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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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with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates, hands on skills in implementation of fusion/learning based techniques in