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scientific computing. Experience running large-scale excited-state simulations on HPC platforms. Excellent record of productive and creative research as demonstrated by publications in peer-reviewed journals
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of the field through the development and use of machine learning, deep learning, and high-performance computing (HPC). This position resides in the Chemical Separations Group in the Separations and Polymer
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response Demonstrated expertise in process development/optimization for macro-scale deformation in AM Experience with multi-physics simulations on high performance computing (HPC) and maching learning (ML
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, and image analysis tools and working on a computing cluster (HPC). Vivid Interest in interdisciplinary research, leading and working on projects with pathologists, medical experts, computer scientists
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
data using Python, R, etc. Preferred Qualifications, Competencies, and Experience Desired qualifications are a) atmospheric and aerosol chemistry, b) proficiency in HPC, and working in a cloud computing
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verbal communication skills, with a strong record of publications in relevant fields. The ideal candidate should have at least 1-2 peer-reviewed research papers published in prominent HPC venues (e.g., SC
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-performance computing (HPC) systems. Proven track record of interdisciplinary collaboration on research projects. Strong publication record in relevant fields such as environmental science, data science, or
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(e.g. Python, R, …). Familiarity to work on a Linux computing cluster (HPC). Preferably experience in working with large medical image data. Vivid interest in the analysis of microscopy images or similar