84 phd-scholarship-for-solid-mehanical-engineering-in-image-processing Postdoctoral positions at Argonne
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the last 0-5 years) in geology, earth sciences, chemistry, chemical engineering, or materials engineering (those with other degrees but have similar skills to those listed will be considered). Experience in
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry, chemical engineering or materials science (those with other degrees but have similar skills to those listed will be
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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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; publish and present high-impact research results Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of materials science, physics, electrical engineering, or a
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of advanced bioleaching processes for recovery of critical minerals from secondary materials The candidate will design and execute experiments; operate, monitor, and troubleshoot bench- and pilot-scale
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, asphaltenes, resins, and kerogen molecules and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will
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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-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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involvement in three SciDAC-5 projects: 1) Femtoscale Imaging of Nuclei using Exascale Platforms, 2) Fundamental nuclear physics at exascale and beyond, and 3) Nuclear Computational Low Energy Initiative
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation