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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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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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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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for machine learning in materials science, you will work in close collaboration with members of the WASP-WISE pilot project on predicting moisture content in timber drying using machine learning
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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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risk indicator for predicting myopia onset in children. Ophthalmic Physiol Opt. 2024; 00: 1–17. https://doi.org/10.1111/opo.13401 Naidoo KS, et al. Potential Lost Productivity Resulting from the Global
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pathogenesis and their potential as therapeutic agents and diagnostic tools. Using in vitro, ex vivo, and in vivo models, the lab studies EVs derived from amniotic fluid stem cells (AFSCs) and other perinatal
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, Chemistry or related scientific fields and experience and knowledge managing and analyzing spectroscopic data to build predictive models. The Successful candidates should be able to work independently, have
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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
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 2 months ago
the form of graphs to analyze and predict food-effector systems. Key Responsibilities Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data Multi-omics integration