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close coordination with project partners, the recruited researcher will conduct experiments to determine the extent to which neural models, now at the heart of many approaches to Natural
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, creating predictive models for failure control. Validation & Experimental Collaboration: Compare simulations with experiments, collaborate on proof-of-concept testing, and refine models based on results
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, numerical methods, and Earth system modeling to develop and evaluate a coupled xylem–phloem transport framework that translates multiscale physics into next-generation vegetation model schemes. Key
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Description Completion of doctoral thesis related to: Process and analyze experimental data. Develop predictive models using deep learning. Train, validate, and optimize neural networks (CNNs, etc.) applied
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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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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, early detection of degradation, and residual life prediction. The program integrates physical modeling, machine learning, and data fusion techniques to optimize predictive maintenance, reduce operating
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modelling. MISSION You will actively contribute to the development and evaluation of new hybrid computational method to predict biological tissue deformation with subject-specific material properties
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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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well as next-generation ecological models that take uncertainty into account. The https://leca.osug.fr (LECA) is part of the University of Grenoble Alpes and the CNRS in France. Grenoble is located close to