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Field
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postdoctoral researcher for pioneering research at the convergence of artificial intelligence (AI) and materials science. The ideal candidate should possess expertise in scientific machine learning (SciML
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] Subject Areas: Artificial Intelligence, Machine Learning and Autonomy Computational Science and Engineering / Machine Learning Computational Biology / Data Analytics Analytical Chemistry / Current
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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Posting Details Posting Details Posting Number 0801675 Classification Title Postdoctoral Research Associate- Autonomous Systems and Machine Learning Working Title Department College
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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Postdoctoral Associate Position on Blockchain and Machine Learning in the Dr. Kuo Lab at Biomedical Informatics and Data Science, Yale University New Haven, Connecticut (USA) About the postdoctoral
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candidates with a proven track record in developing open-source machine learning, deep learning, or cheminformatics tools (Preferred written in Python). Job Duties Plans, directs and conducts research
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how circuit structure supports computation. Will lead research on one or more of the following areas: Automated proofreading & annotation at scale: Machine learning approaches for error detection, human
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer