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experience coding in Python and R. Strong understanding of algorithms, data structures, and computational theory. Experience with data analysis and visualization tools to interpret simulation results. Ability
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equivalent experience (e.g. graduate school or industry experience). • Substantial experience coding in Python and R. • Strong understanding of algorithms, data structures, and computational theory
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applications from all areas of experimental and theoretical/computational bioengineering. We particularly encourage candidates whose work includes aspects of Device Bioengineering and/or Computational
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with compiler level languages, accelerated computing (preferably with OpenMP or OpenACC) and distributed computing (MPI). A thorough understanding of the particle-in-cell algorithm, its inherent
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The Computational Turbulent Reacting Flow Laboratory, led by Prof. Michael E. Mueller, invites applications for postdoctoral or more senior research positions in the field of atmospheric aerosol
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econometric analysis and preparing results tables, managing large data sets, handling spatial data, applying machine learning algorithms, conducting computationally intensive statistical analyses, summarizing
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Learn the underlying science, mathematics, statistics, data analysis, and algorithms of computational research questions through independent research, studying existing code bases, and staying current
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media including Facebook, Twitter, Instagram, YouTube, LinkedIn, and TikTok as well as excellent understanding of algorithms and platform best practices. - Storyteller at heart with strong writing skills
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machine learning algorithms, conducting computationally intensive statistical analyses, summarizing research findings, and editing research papers. In addition to working closely with faculty, senior
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research in PPPL-relevant AI4Science topics. The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied