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to effective therapeutic strategies targeting IDPs Collaborate on the development of open-source machine learning tools to support these therapeutic designs Work closely with high-throughput screening teams
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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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field Experience leveraging artificial intelligence or machine learning in the development of battery electrolytes and catalyst materials Demonstrated expertise in lithium–sulfur battery materials and
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference
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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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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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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning