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. Description: This project will develop a multimodal artificial intelligence framework to characterize and predict dynamic changes in forest structure, aboveground biomass, and carbon storage under hydroclimatic
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model introduced previously for carburizing will be further developed in this study. In this model, carbon diffusion is predicted using Fick's law and finite difference scheme. A source term accounts for
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. Developing predictive models for precision oncology: We leverage large-scale multimodal datasets, including molecular profiling, clinical records, imaging, and longitudinal treatment histories, to develop
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: www.zhuhlab.com The candidates will focus on one or two of the following projects: Developing predictive toxicity models for assessing new environmental pollutants, nanoplastics, and environmental mixtures
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, biomedical data science, digital health, epidemiology, and environmental health. The position focuses on the development, validation, and interpretation of AI models for health risk prediction using
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Summary Seeking one motivated MS engineering student to support a research project on real-time refractory thickness measurement using thermal sensing, inverse heat-conduction model, and 3D
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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: www.zhulab.com The candidates will focus on one or two of the following projects: Developing predictive toxicity models for assessing new environmental pollutants, nanoplastics, and environmental mixtures
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investigates the thermodynamic modelling of chloride migration in concrete exposed to accelerated chloride ingress conditions, with particular focus on replicating and predicting the results of the NT Build 492
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-driven mathematical modeling in a transdiagnostic clinical cohort. https://impact-mh.org/awardees/impact-mh/ IMPACT-Y is collecting repeated measures from approximately 2,400 individuals across multiple