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. This PhD will focus on uncertainty-aware machine learning models, developing and evaluating techniques (e.g., Bayesian and interval neural networks) to quantify model uncertainty and monitor it during
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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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on quantitative phenotyping via generative modelling of quantitative MRI data. This exciting PhD position combines advanced machine learning with medical imaging physics to develop next-generation tools
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Learning, or a related field. A Master’s degree is preferred. ASR/TTS Expertise Experience in training and fine-tuning Automatic Speech Recognition (ASR) or Text-to-Speech (TTS) models, preferably in
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language models from LLMs. Demonstrated publication record in the machine learning and AI field. Excellent programming and computer science skills. Preferred Qualification: Doctoral degree in electrical
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of physics- informed machine learning and deep learning, with applications to inverse problems in scientific imaging and the modeling of complex physical systems. The overall goal is to integrate the knowledge
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. Demonstrated experience applying statistical modeling and/or machine learning methods to research problems, e.g., text mining, natural language processing, image segmentation, voice recognition, etc. Knowledge
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FieldMathematicsYears of Research Experience1 - 4 Additional Information Eligibility criteria - Thesis in natural language processing with machine learning, - mastery of NLP and machine learning methods and tools
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As a component of the faculty cluster initiative, the Chancellor’s Faculty Excellence Program , NC State University is recruiting one tenure track Assistant Professor in mathematical modeling/machine
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical