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monitoring in manufacturing environment Develop modular, extensible workflows for data processing Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal
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field Demonstrated expertise in one or more of the following areas: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including
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/PhD degree with a focus on Metabolism, Mouse Models systems, Human stem cell systems, Biochemical and Molecular Tools, Epigenetics, Genetics, Genomics, Biology, Bioinformatics, Machine Learning, or a
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have demonstrated experience applying AI and machine learning tools to manage, clean, and code complex nutrient content and food product datasets. Experience with data visualizations, front of pack
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory
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Position Information Posting Number F00783P Position Title Postdoctoral Research Associate Department Physics Location Arlington Job Family Faculty Position Status Full-time Rank Post-Doc Work Hours
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Requisition Id 16723 Overview: We are seeking a Postdoctoral Research Associate with expertise in artificial intelligence (AI) and machine learning (ML) for multiscale physical systems
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industry-sponsored capstone projects. With a versatile curriculum spanning software, systems design, nanofabrication, and machine learning, the program prepares graduates to drive progress in fields like
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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. Experience with developing machine-learning surrogates for structure-property relationship, generative AI models, material representations, machine learning force-fields (especially extensions to spinful