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: Textual Prediction of Survival (LLM classification & Attention Modelling) This project develops a model to predict patient survival by analyzing heterogeneous clinical documents. Unlike traditional methods
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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accepted all year round Details Dynamic optimization is integral to many aspects of science and engineering, commonly found in trajectory optimization, optimal control (e.g. model predictive control, MPC
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods
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to apply Website https://www.academictransfer.com/en/jobs/357797/post-doc-opening-predictive-con… Requirements Specific Requirements Required Qualifications: PhD in Robotics, Control, Mechanical Engineering
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processes, targeting annual savings of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real
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identification, i.e. learning of models from measured data, and iii) real-time control, e.g. using the model predictive approach. We are working on several projects with industrial partners across the energy
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of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real-time data acquisition. You will
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represent a major environmental and public health challenge, affecting water quality, aquatic biodiversity, and human uses. The research work will focus on the detection and prediction of these algal blooms
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, “Time-Varying Operator-Theoretic Framework for Tipping Point Prediction” (PI: Prof. Sho Shirasaka) in the JST PRESTO research area “Exploration of New Science Using Mathematics to Predict and Control