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, technique development, and new initiatives to peer reviewers and Q-NEXT program managers. Position Requirements Completed Ph.D. within the last 0-5 years (or soon-to-be-completed) in condensed matter physics
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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant
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among material properties, electrochemical performance, and battery system cost at the material, cell, and pack levels. The researcher will plan and advance performance and cost modeling of energy storage
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for the successful candidate and illustrates the general nature of the work but is not intended to be exhaustive. In addition, the successful candidate is encouraged to bring their inputs in the research direction
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completed in a relevant field of study. Experience with deep learning (DL) frameworks such as PyTorch, TensorFlow, or JAX. Strong programming proficiency in Python. Demonstrated experience with coherent X-ray
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foundation model methodologies, with federated learning serving as a key enabling research direction. The postdoctoral researcher will be advised by the principal investigator, while being expected to exercise
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
). Proficiency in scientific programming (Python, MATLAB, or equivalent). Ability to work effectively in a multidisciplinary, multi-institutional collaboration. Excellent written and oral communication skills
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on experiment progress, technique development, and new initiatives to peer reviewers and Q-NEXT program managers Position Requirements Completed Ph.D. within the last 0-5 years (or soon-to-be-completed) in
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Hands-on experience with two-dimensional materials modeling Proficiency in database development and management for computational materials data Strong programming skills and experience with software