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mechanics, machine learning or applied/computational mathematics. ● Demonstrated ability to carry out original mathematical derivations and/or develop computational tools, evidenced by publications
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analysis, machine learning, mathematics of data scienceMathematical modeling and manifold learning of high-dimensional data geometry, with theoretical foundations and applications in evolutionary biology and
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start date. Preferred Qualifications: Research experience in computer vision, NLP, geospatial data systems, or high-performance computing. Brief Description of Duties: The Postdoctoral Associate will
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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technologies. The candidate will work at the intersection of Artificial Intelligence, Scientific Machine Learning, and Energy Materials, contributing to the design of self-driving laboratories and no-code
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brain MRI analysis, statistical analyses, as well as data acquisition and machine learning. Experience with stroke and federated learning is a plus. Job ID REQ20177725Posted Date 08/05/2026 Current
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microscopy. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master
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students from across the nation for future careers in the STEM workforce. All eligible candidates are encouraged to apply. Program Contact Want to learn more about the MLEF Program? Register for one of our
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, measurement, and evaluation strategy, with a focus on cross-sector data infrastructure, linkage, performance measurement, evaluation, and continuous learning. Responsibilities: 1. Serve as a scientific partner