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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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industrially-relevant human-made materials. This project will address key priorities in the microscopy sector by developing workflows that integrate cutting-edge imaging and characterization techniques and
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The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship fully funded by the department to commence on September 2025 or as soon as possible thereafter
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lives, appearing in processes such as in additive manufacturing, the Earth’s atmosphere, and inkjet/biomaterial printing. The key to understanding (and ultimately engineering) these applications is how
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as Physical Geography, Geology, or Engineering Geology, with a numerical background in earth surface processes. Field experience and skills in GIS and programming skills are necessary. The scholarship
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sensors to understand their local surroundings at sea and inform optimal action. To ensure safety requires the ability to reliably detect, image and recognise their environment, in terms of surrounding sea
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per year for 3.5 years. Lead Supervisor’s full name & email address Dr Massimiliano Fasi: m.fasi@leeds.ac.uk Project summary The growing importance of artificial intelligence is fostering a paradigm
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, Computer Sciences or Aerospace Engineering or a related discipline; a Masters degree in these subjects would be of advantage. In addition, applicants should be able to demonstrate an interest across
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We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only
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Project Link: Preclinical Evaluation of Spinal Therapies | Project Opportunities | PhD | University of Leeds Number of Positions: 1 Funding: School of Mechanical Engineering Studentship, in support