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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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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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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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-speed cameras (in a newly renovated lab dedicated to our research group). A significant component of the analysis will include image processing, including data-driven methods and machine learning. You
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for these infants. Structural brain imaging with cranial ultrasound (CUS) and magnetic resonance imaging (MRI) remain the traditional means of neurological assessment but are limited in their ability to reliably
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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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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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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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Nikon Imaging Centre (The Wohl Cellular Imaging Centre), are part of the UK Motor Neuron Disease Research Institute and work closely with researchers in the UK Dementia Research Institute. Dr Sreedharan
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mitigation system. Understanding the process of droplet impact and freezing dynamics at high airspeeds, on textured and non-textured surfaces is critical to deciphering the physics behind ice adhesion and