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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
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, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI
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capabilities. Key Responsibilities: Capturing requirements and analyzing specifications for future detector systems Performing conceptual design and system-level optimization using emerging computing
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The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
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Argonne National Laboratory is seeking a highly skilled Postdoctoral Researcher to work in the Applied Materials Division (AMD). In this position the successful candidate will conduct applied
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years ) Ph.D. in Engineering, Operations, Computer Science, Mathematics or a related field. Knowledge of optimization, power systems operations and planning, electricity markets, issues surrounding
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define requirements and performance specifications for future HEP/NP detector systems Perform detector concept development, system-level design, and optimization leveraging emerging computing architectures
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We invite you to apply for a Postdoctoral Appointment with Argonne’s Electrochemical Materials and Interfaces Group in the Materials Science Division. The purpose of this appointment is to perform
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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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