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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer architectures for science Developing and advancing
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-efficient computing Developing mathematical modeling for complex scientific problems Designing algorithms to improve the performance of scientific applications Researching digital and post-digital computer
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& Bioinformatics, is seeking candidates for a postdoctoral research fellow position. This is primarily for an NIH-funded project developing multimodal variational autoencoder models and probabilistic trajectory
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on the littoral environment. Algorithm development includes photogrammetric measurements of wave parameters, image stabilization, and use of AI/ML models for image segmentation and classification. Algorithms will
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to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross
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, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models, with objectives to amplify
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, reinforcement learning, and computational game theory to address this gap. Fellows will contribute to advancing the next generation of models, algorithms, and system architectures for autonomous systems, multi
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learning, and data science, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms