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(End Date of Assignment, Project, or Grant) 09/30/2026 Position Type Faculty Job Family Faculty Position Overview Computational Combustion Laboratory (CCL) at Marquette University is recruiting a
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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conferences to disseminate research findings, and mentoring junior team members in preparation for their presentations. In parallel, the principal investigator (PI) will provide mentorship aimed at supporting
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(CHX, 11-ID) beamline at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced
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is a highly collaborative, creative, and fun group of scientists at St. Jude Children's Research Hospital. Our research program centers on the development of state-of-the-art genomic methods
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 21 days ago
; strong physical, mathematical, and computational background; experience with programming in at least one general-purpose language (preferably Julia) and parallel computing; demonstrated effective written
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; strong physical, mathematical, and computational background; experience with programming in at least one general-purpose language (preferably Julia) and parallel computing; demonstrated effective written
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National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more
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parallel computing techniques including working in the cloud. Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications section. Certifications
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse