540 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof" PhD positions in United Kingdom
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continuous lifetime treatment. Recent efforts to cure HIV infection have focused on developing latency reversing agents as a first step to eradicate the latent reservoir and animal models are being studied
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
system health monitoring, and more efficient maintenance planning. Digital twins offer a powerful foundation but must evolve beyond simulation to truly support engineering decisions. This PhD will develop
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training and development to enable adaptable, sensitive and authentic music teaching within culturally diverse communities. The supervisory team will include Dr. Robert Gardiner (Robert.gardiner@rncm.ac.uk
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development with a focus on aerodynamics. The role is for the 2nd cohort of the EnergHy programme which commences in October 2025. Research project overview: The X-Rotor is a radical offshore wind turbine
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, biochemical and molecular biological approaches. You will develop the necessary skills to derive experimental data that could identify important roles for these molecules in glioma progression and that may
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to develop enhanced NbS strategies that target micropollutant removal and remain compatible with other ecological and environmental benefits. The aims of this project are therefore to 1) benchmark the long
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communities in the midst of civil war in addition to sustained strikes and new political movements. At its broadest perspective, the project aims to develop resources with which to consider the pasts, presents
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, an innovative low-pressure airtightness testing technology co-developed by the University of Nottingham and Build Test Solutions Ltd (BTS). This is a fantastic opportunity to work towards a PhD whilst working
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-world problems in the built environment. The project will advance the capabilities of Pulse, an innovative low-pressure airtightness testing technology co-developed by the University of Nottingham and
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these challenges by combining advanced metrology, data science, and machine learning to develop predictive models and new standards for recycled plastics. Based at the University of Manchester, in collaboration with