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clustering, redshift-space distortions, weak/strong gravitational lensing, and artificial intelligence/machine learning (AI/ML). The observational focus is on optical sky surveys (DES, DESI, Roman, Rubin Obs
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We are seeking creative Postdoctoral researchers to bridge the gap between leadership-class supercomputing and cutting-edge open science in the area of AI and Machine Learning. Successful candidates
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We are seeking a highly motivated Postdoctoral Appointee with a strong background in artificial intelligence and machine learning (AI/ML), with particular emphasis on the development and application
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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contribute to the Lab’s broader effort in conversion and separation of carbon-based materials. The role will require the individual to work with personnel that perform machine learning and molecular
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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python
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to study chemical transformations in materials. 2. Artificial Intelligence Applications: - Leveraging conventional machine learning techniques for materials property prediction and Bayesian approaches
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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++, or JavaScript Experience with AI or machine learning techniques, including large language models or agentic systems Experience developing or integrating interactive visualization systems, including web-based