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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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road conditions. Your specific activities will include (but are not limited to): • Develop robust, production-grade machine learning solutions for predictive modelling and complex decision
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monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning. Develop and evaluate GPT-powered AI
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for interacting with colleagues and stakeholders. Department Specifics: Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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for interacting with colleagues and stakeholders. Department Specifics Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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decision-making for complex infrastructure systems. This position offers an opportunity to contribute to interdisciplinary research at the intersection of civil engineering, machine learning, and systems
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computer applications used for data recording, analysis, and reporting. Physical Demands and Working Conditions Physical Activities Working Conditions Additional Information Remote Work: A hybrid remote work
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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materials used in defense applications. Online monitoring of additive manufacturing requires a deep understanding of process conditions and microstructural evolution, which can be modeled through machine