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believe that generative pre-training offers a promising path to a new class of models that work across settings and can support prediction of many different clinical outcomes at once. To fuel your models
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wide variety of translational neuroscience research programmes. The focus of the role will be analysis of large clinical datasets from PRECISION-ALS (n~20,000) and PRO-ACE to develop prediction models
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position in the area of Learning, Optimization, and Decision Analytics. SCAI (https://scai.engineering.asu.edu/ ), one of the eight Fulton Schools, houses a vibrant Industrial Engineering and Computer
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of mold free shelf-life predictive models, determining the number of variables as well that need to be recorded to be able to train the model; (ii) design and development of a model to predict mold growth
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to this research line, planning protocols, overseeing data collection, facilitating communication between teams, and ensuring ethical and regulatory compliance. Implement data-analysis models to predict cognitive
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a variety of applications in advanced manufacturing and defense. This is a DMEx funded project. Predicting these mechanisms is a complex mathematical problem that involves the solution of a framework
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, development, and evaluation of a digital twin model for on-site, renewable-driven green hydrogen generation systems. The successful candidate will contribute to an industry-sponsored applied research project
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these challenges by: Developing predictive workload, lead-time estimation, material planning models to capture the high variability in HMLV environments using hybrid AI (combining machine learning, feature-based
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Your Job: You will be a member of a consortium of leading research institutes and an industry partner. Your task is the build-up of a predictive model for tandem cell stability. Your tasks in detail
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FLAME-GPU accelerated agent-based modelling of material response to environmental and operational loading EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce