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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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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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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative
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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce
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optical setup construction. They will make use of commercial simulation software to test electromagnetic designs, algorithmic coding to design metamaterials, fabrication techniques to produce
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to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
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workspaces under positional restrictions. Develop smart control algorithms that will allow the robotics end-effectors to communicate with the central control system and coordinate tasks with other end
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-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability