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Intelligence, Machine Learning, Quantum Information and Quantum Simulation. The successful candidate will be expected to lead an independent research program in particle theory to strengthen and complement
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The Nuclear Science and Engineering (NSE) Division is seeking a postdoctoral appointee to develop computational methods and computer codes to model the physics and engineering of advanced nuclear
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looking for candidates whose research program aligns with the 2023 Long Range Plan for Nuclear Physics, focusing on lab-based tests of fundamental symmetries via precision experiments. The ideal candidate
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A position in theory and computational modelling in the Non-Equilibrium Soft and Active Matter group in the Materials Science Division is now open. We encourage applicants working in soft, polymeric
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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The Multiphysics Computation Section within the Transportation and Power Systems Division at Argonne National Laboratory is seeking to hire a postdoctoral appointee. The successful candidate’s
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-inspired research relevant to microelectronics. The candidate will be part of a highly interdisciplinary project involving X-ray scientists, physicists, materials scientists, and computational scientists
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of deposition science and heterogenous interfaces. Position Requirements: A PhD in chemistry, materials science or related field; received within the last 5 years or upcoming year. Significant written and oral
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(predoctoral) or PhD (postdoctoral) in Materials Science, Chemistry, Physics, or related area is required. Coursework in computer science or data science is desirable. Familiarity with research data management