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and social care research (Prof. Anderson), applied statistics and analysis of large routine datasets (Prof. Abel), and substantive knowledge of the abuse of older people and related policy issues and
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling
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-driven algorithms which can solve state estimation problems in fluid mechanics, such as inferring the instantaneous state of a fluid’s velocity field from sensors embedded in its boundary. The research
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abort (or not engage) if the bright white lines that fit a defined and rigid expectation are not clearly visible. These systems use algorithms, rather than AI machine learning, to detect road markings and
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is also desirable. The project will be based at the Institute for the Science of Early Years (www.isey.org ) in London, UK. Supervision will be by Prof Sam Wass (www.profsamwass.com ) (UEL, UK), with
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Early Years (www.isey.org ) in London, UK. Supervision will be by Prof Sam Wass (www.profsamwass.com ) (UEL, UK), with Prof Davidson (UEL, UK), Prof Rachel Barr (Georgetown, US) and Dr Sarah Jessen
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be by Prof Sam Wass (www.profsamwass.com ) (UEL, UK), with Prof Davidson (UEL, UK), Prof Rachel Barr (Georgetown, US) and Dr Sarah Jessen (Lübeck, Germany) as co-supervisors. The PhDs will start in
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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, dynamical systems and statistical physics. The candidate will be jointly supervised by the Coventry team Dr Fei He and the Stellenbosch team Prof. Francesco Petruccione . This project will contribute