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candidate (m/f/d) for the “Development of a digi-tal twin and model predictive control for filtration processes”. Project Join a research initiative in the field of Industry 4.0 and cyber-physical systems
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AstraZeneca and Newcastle University , will develop predictive models for pharmaceutical manufacturing and provide access to industrial data and high-performance computing facilities. You will gain expertise
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Position Details Position Information Internal Posting? Posting Number SP005013P Position Title Postdoctoral Research Associate, Predictive Modeling for Mental Health Outcomes Division/College
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. Machine-learning and deep-learning techniques will be developed and compared for cancer-risk prediction, classification and prognostic modelling. Explainable and Multimodal AI Explainable AI (XAI) methods
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to predict diabetic foot complications, peripheral neuropathy, peripheral arterial disease and amputation risk. Prediction and Decision Support The research will develop interpretable predictive models
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for socially intelligent embodied agents. The central idea is to build predictive models that jointly represent people, the surrounding environment, and the actions of the embodied agent. Information from video
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are computationally expensive, making them clinically impractical at scale. The solution lies in image-based, data-driven (AI) models that learn to predict personalised fracture risk directly from routine bone-density
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, and advance diagnostic timelines to improve overall survival outcomes. 2. Data Preprocessing & Predictive Modeling The study utilizes multi-modal clinical and laboratory data, integrating basic
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directions include: ● Generative models of cell–cell communication . Move beyond descriptive ligand–receptor analysis to models that predict and help understand how cells react to signaling cues. ● Joint
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of response and develop predictive models. The work will involve analysis of large-scale datasets through multiomics integration, machine learning, statistical genetics, QTL analysis and development of genetic