10 wireless-sensor-network PhD positions at University of Nottingham in United-States
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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, the University of Nottingham provides the perfect environment to carry out high-impact research that can genuinely shape the UK’s Net Zero future. This is your opportunity to create breakthrough materials
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the perfect environment to carry out high-impact research that can genuinely shape the UK’s Net Zero future. This is your opportunity to create breakthrough materials for clean energy technologies and develop
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to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
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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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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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technological advances that support the global transition toward net-zero emissions and sustainable aerospace engineering. Motivation The reliability of electric propulsion systems is pivotal for next-generation
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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discussion regarding the PhD. This is an excellent opportunity for an enthusiastic graduate to build a strong skillset in interdisciplinary research and a collaborative network with both academic and