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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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The Vehicle Technology Assessment (VTA) Group within the Vehicle and Mobility Systems at Argonne National Laboratory is seeking to hire a postdoctoral appointee to assess vehicle technologies
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”, “Firstname_Lastname_cover_letter”. Include links to code examples in your CV (e.g., GitHub page, past project repositories). Position Requirements A recent PhD (completed within 5 years, or soon to be completed) in computer science
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recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Computational Materials Science, Chemical Engineering or a closely related field. 2. Technical Expertise
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The Applied Materials Division (AMD) at Argonne National Laboratory is looking to hire a Postdoctoral Appointee – Materials Science. The Applied Materials Division conducts applied research
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, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven scholarly work or industry
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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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. Position Requirements Ph.D. completed in the past five years or soon-to-be completed in Chemical Engineering, Materials Science, Chemistry, Nuclear Engineering, or related field. Skill in devising and
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formal education in chemical engineering, chemistry, materials science, nuclear engineering, mechanical engineering, or related field at the PhD degree level with zero to five years of experience
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apply funding from federal agencies (e.g., the Department of Energy and National Science Foundation). A successful candidate should have a solid background in power system engineering, optimization