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The Chemical Sciences and Engineering Division is seeking applicants for a postdoctoral appointee who will conduct computational research in Selective Interface Reactions (e.g., atomic layer
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3 years) in computer science, materials science, chemistry, physics, mathematics or related engineering disciplines Knowledge of deep learning techniques for time-series and image data Experience with
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) in the field of accelerator physics or a closely related science and engineering discipline Strong experience developing and applying computational modeling and simulation Familiarity with accelerator
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, and engineers specializing in electron and X-ray microscopy, fostering a collaborative, inclusive, and high-performance culture Advance the CNM user science program, enabling cutting-edge experiments in
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staff members, two engineers, and postdocs and students. Our program spans electron-scattering experiments at Jefferson Lab in Hall A, B, and C, including CLAS12 and SoLID. We have led SeaQuest and are
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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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enzyme engineering workflows on their respective leadership computing platforms. Key Responsibilities: Design and implement generative AI models and agentic systems capable of scientific reasoning and
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-completed PhD (typically completed within the last 0-5 years) in chemical engineering, environmental engineering, or similar degree. Experience with data collection, processing, analysis, and presentation
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The Q-NEXT National Quantum Information Science and Research Center based at Argonne National Laboratory invites applications for a postdoctoral position to conduct research in the field
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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence