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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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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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developmental biophysics, imaging, image analysis, and modelling of biological processes. Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their
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materials and energy-intensive manufacturing processes. These machines dominate current electric powertrain solutions but pose challenges in terms of resource supply chain, recyclability, and embedded carbon
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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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diffusion models usually needs to access a pre-trained model multiple times sequentially to generate high-quality images or videos, which is time-consuming. The training process of diffusion models is also
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PhD Studentship: Towards Sustainable Powertrains: Enabling High Motor Performance without Rare Earth Materials and Energy intensive Manufacturing Processes The University of Nottingham This project
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Supervisors: Dr Abhay Vincent This is a fully funded PhD (fees and bursary) in experimental icing research. Fundamental understanding of droplet impact dynamics is integral to icing. The overall aim
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resolution images of small targets. The PhD project will include a number of fundamental and experimental studies related to the ability to generate focused radar imagery in sea conditions, by developing
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the sites to normal use. X-ray backscatter imaging is a non-destructive analysis technique, where X-rays are directed at a target and Compton/back-scattered photons imaged. Existing industrial systems with