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of Professor Adélio Miguel Magalhães Mendes. Grant duration: Initial duration of 3 months, with the predicted starting date in February 2026, on an exclusive basis eventually renewable but never exceeding
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Monitoring Duties & Responsibilities: Build early warning and clinical deterioration prediction models Develop continuous clinical risk trajectory modeling frameworks Model time-series data such as vitals
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, surveys, faculty research, and business intelligence programs. Provides strategic direction for dashboards and predictive modeling, empowering leadership with real-time insights and key performance metrics
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Kogias as part of his ERC Starting project titled CloudNG (https://cordis.europa.eu/project/id/101220079 ). The post will be based in the Department of Computing at Imperial College London at the South
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the specific characteristics of viscoelastic fluid models, which will provide a dataset for training the tensor-based neural network (TBNN). Subsequently, the TBNN model will be tested on deformation protocols
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field. This approach is related to data assimilation, allowing for better prediction, control, and optimisation of turbulent systems in engineering, energy, and environmental applications
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on stability. Testing the model in standard stirred tank apparatus Refining the model to allow predictability between different types of apparatus. Defining an algorithm for testing enzyme stability
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monitoring. • Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions. • Analyze and optimize structural performance and predictive
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experimental design. Deep expertise in predictive modeling, classical ML algorithms (e.g., decision trees, gradient boosting), large language models (LLMs), generative AI, MLOps, and AutoML using frameworks like
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, Griffith J et al A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure. JAMA. 2011;305(15):1553-1559. Runx1 and Heart Failure Supervisors: Dr C Loughrey , Dr S Nicklin , Ewan Cameron