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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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, computers and instrumentation hardware. Ability to install and oversee installation software algorithms for distributed controllers and maintain associated databases. Ability to coordinate maintenance and
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the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability
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development and application of novel algorithms and machine learning/AI techniques for extracting insights from biological data sets (genomics, proteomics, imaging, neuroscience), and related areas
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, Python, Julia, and/or MATLAB Familiarity with machine learning methods and algorithmic modeling for large datasets Experience with LaTeX, Unix/Linux Evidence of outstanding academic achievement Familiarity
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and follow projects through to completion. PREFERRED QUALIFICATIONS Knowledge of STATA, R, Python, Julia, and/or MATLAB Familiarity with machine learning methods and algorithmic modeling for large
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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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Engineers. Serve as liaison with Princeton Research Computing staff on GPU cluster related issues. Professional Development Learn the underlying science, mathematics, statistics, data analysis, and algorithms
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to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability sciences. Whether it be through science, engineering, technology or professional services, every team