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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in atomic layer deposition of thin films, in situ metrology, interface science
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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This is an opportunity for a knowledgeable and creative individual to be part of a team developing advanced humanoid and dexterous robotic capabilities for scientific use-cases. Recent progress has
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teamwork. Strong background in quantum emitter-based defects, quantum networking, and quantum information science is preferred Experience with fiber device packaging is highly advantageous but not required
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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in experimental condensed matter physics. Although exceptional candidates in
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: Define Your Contribution: We understand that science is often collaborative. In your CV and cover letter, please clearly distinguish your individual contributions from the group's achievements (e.g
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, written, and oral communication skills. Experience with molten salt systems, actinide chemistry, or electrochemistry is desired, but not mandatory. Experience working safely with hazardous materials in
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scale up (0.5 to 400 L) arrested methanogenesis systems to convert diverse low-value organic waste streams into value-added products (e.g., carboxylic acids), and support the development and scale-up
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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
, large-scale computational science, and simulation of networked physical systems Familiarity with techniques for sensitivity analysis and handling high-dimensional problems Experience in power grid