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develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung infection. As part of this work, the postholder will
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interpretable machine learning (IML) and nonlinear system identification approaches. In doing so, we will build transparent, interpretable, parsimonious and simulatable (TIPS) models to help identify the causes
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malignant precancerous lesions in the mouth. To facilitate the machine learning model building, the virtual oral tissue models will be developed based on knowledge derived from tissue-engineered constructs
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of the art 20,000m² Diamond Building, you’ll be inspired by what we can offer our Engineering students. We have world leading facilities in teaching and learning, with 15 specialist laboratories designed
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applications, for example Word, Excel and Google networked office applications. Experience of using computer based financial systems, for example SAP. Excellent Customer service skills, with experience
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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
AI-assisted adversarial attacks. You will work on topics such as cybersecurity, intrusion detection, adversarial machine learning, industrial automation, digital twin technology, and reinforcement
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markers. Develop machine learning models capable of predicting Category 1 emergencies based on real-time audio features extracted from calls. Work iteratively with YAS researchers to test and refine
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for workshops, liaising with wider team and professional services staff to place orders as necessary. Drive the project van to and from events where required. Ensure all equipment, resources, and machines
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will involve designing innovative QML approaches and collaborating