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simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis optimization. AI/ML methods development: Neural networks, graph neural networks (GNNs), generative
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, diesel generators, and other sources. Implement predictive, rule-based, or optimisation-based control strategies using MATLAB/Simulink, Python, or embedded software tools. Integrate controller logic with
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Efficient Quantum Architectures. arXiv preprint arXiv:2508.05339. Nugraha, F. P. and Shao, Q. (2023). Machine Learning-Based Predictive Modeling for Designing Transmon Superconducting Qubits, 2023 IEEE
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analytical tools, coupled with advanced crop modelling techniques so to evaluate the effectiveness and predict outcomes of various crop production strategies. To develop a strategic vision of the agricultural
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phenotypic, genotypic, and environmental data to build prediction models for key traits of blueberry such as flowering time, yield, and fruit quality. This position reports to Dr. Sushan Ru at Auburn
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deep learning models (e.g., adapting methods in [6]) based on spatial cellular graphs constructed from these images to predict clinical outcomes. The research will be carried out using two
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the collection of empirical data through field trials and the development of prediction models based on these data. The candidate is to perform a variety of functions related to research. The candidate is expected
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the collection of empirical data through field trials and the development of prediction models based on these data. The candidate is to perform a variety of functions related to research. The candidate is expected
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include applications of neural networks to the analysis of multi-omic data, models for predicting phenotypes using genotype data, biological data integration, etc. Participation in these projects will
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the creation of accessibility letters for student-athletes with disabilities. Work with the office of Enrollment Management to use a data model that aids in the prediction of student success and encourages a