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policy, environmental science, 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
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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
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have the opportunity to be a part of a world-class scientific team and lead tasks in vigorous research programs. Position Requirements A PhD in Physics, Materials Science or a related field; received
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, integration of other emerging technologies, and interdependencies between power grid, transportation, and water systems. This position may require domestic and international travel. Provides support to develop
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of Pittsburgh, University of Texas Medical Branch and BARDA, aimed at advancing pandemic bio-preparedness through AI-driven forecasting. With advances in machine learning frameworks and emerging accelerator
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national security. With guidance, the appointee will: Develop and implement processes for chemical separations for nuclear-energy relevant and other industrial chemical applications Develop tools and
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during the application process. Any further questions regarding this position should be addressed to Dr. Peter Mueller (pmueller@anl.gov ). Review of applicants is ongoing and will continue until
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the cleanroom with standard nanofabrication process flow Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range
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using software, such as LAMMPS, and machine-learned potentials Experience in GPU programming with Kokkos An understanding of computer architecture and experience in the analysis and improvement