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https://www.sems.qmul.ac.uk/research/studentships/674/net-zero-natural-resource-energy-and-time-efficient-manufacturing/The PhD work will benefit from access to unique facilities including
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Mission-Inspired priorities of Engineering Net Zero and Artificial Intelligence. This vision also reflects RCA’s institutional research priorities: Climate Crisis and the Circular Economy, and Design & AI
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the University of Nottingham, contributing to cutting edge research into clean and sustainable energy technologies. Vision and Aim Ammonia is an essential component of the global strategy to achieve net-zero
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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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or industry. Network-wide Training Events will provide complementary knowledge, multidisciplinary experience, and transferable skills: ethics & research integrity, scientific writing, communication
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real-world challenges. We work with an extensive network of industrial partners including BT, Haleon and Tesco. Engage with our network of charitable partners Students have the opportunity to engage with
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South and East Network for Social Sciences (SENSS) and CAM-DTP are pleased to announce a call for two ESRC-funded studentships. The purpose of this joint scheme is to promote collaboration between
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management experience across multiple industries, build an extensive professional network spanning academia and industry, and cultivate commercial awareness that enhances your career prospects. Alumni from
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and communication skills. Funding Self-funded/partially funded Please contact the supervisor for more information or explore our funding finder . Cranfield Doctoral Network Research students
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based