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therapeutic discovery and providing commercial growers sustainable methods to meet increasing global food demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric
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, green finance, ethical supply chains, and behavioural change. Digital and Technologies: AI and machine learning, cybersecurity, spatial intelligence, robotics, human-computer interaction, and digital
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language requirement of the UK HEI; Have a background or a proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate
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operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process
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not yet competitive for 5-year clinician scientist fellowships. This post is designed for applicants with a research interest in machine learning or data science approaches for patient stratification
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calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to Level 4 Spine Point 28 - 30
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data to address priority questions in cancer care pathways, diagnostic delay, and treatment access. The role will involve advanced quantitative analyses, such as survival modelling, machine learning, and
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. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches, into simulation design. Conduct
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innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision making. The project will provide
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skills