14 cloud-computing-"https:"-"https:"-"https:"-"St"-"St" PhD positions at Loughborough University
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Imagine a world where sensors don’t just collect data, they think. With the exponential growth of the Internet of Things (IoT) and edge computing, the demand for ultra-low-power systems that can
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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dynamic, optically unpredictable environments, dominated by waves, specular reflection, cloud-dependent illumination, and variable scattering. These factors significantly degrade sensor reliability, leading
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of real-time adaptive 3D inspection, dynamically adjusting its measurement strategy based on data quality as well as environmental and scene cues. Positioned at the intersection of robotics, computer vision
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manufacturing sectors, from SMEs to large global manufacturers. For details, visit the MTC website . Entry requirements: A 1st or high 2:1 degree in computer science, manufacturing/industrial engineering, data
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computational lung modelling. Working with our proprietary respiratory system model, you will generate large-scale, high-quality virtual airflow and acoustic datasets. You will then develop and train state
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supervision from a leading expert in Rolls-Royce throughout the project. How to Apply: All applications should be made online . Under Campus, please select ‘Loughborough’ and select Programme ‘Mechanical and
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, please select ‘Loughborough’ and select Programme ‘Mechanical and Manufacturing Engineering’. Please quote the advertised reference number * CSC-26-WS * in your application under the ‘Finance’ section
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University. How to Apply: All applications should be made online via the above ‘Apply’ button. Under programme name, select ‘School of Social Sciences and Humanities’. Please quote the advertised reference
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the above 'Apply' button. Under programme name, select ‘School of Social Sciences and Humanities’. Please quote the advertised reference number, ‘FCDT-26-LU2’, in your application. This PhD is being