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interpreted using Python and R. Many tasks are performed using Princeton’s high performance cluster computers. Data Collection and literature review: This position will give assistance to Princeton University
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science skills. Large datasets comprising up to many millions of data points are compiled, cleaned, processed, analyzed and interpreted using Python and R. Many tasks are performed using Princeton's high
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practical exams. Assist with weekly data analysis, including: uploading and collating undergraduate data formulating and inputting equations for appropriate data transformation graphing with Excel and R
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or higher in neuroscience, biology, engineering or a related field is required. - 2+ years experience in a wet lab research setting. Preferred Qualifications: - Familiarity with Matlab, Python or R for data
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required. - 2+ years experience in a wet lab research setting. Preferred Qualifications: - Familiarity with Matlab, Python or R for data analysis - Research experience involving neuroscience methods
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inputting equations for appropriate data transformation • graphing with Excel and R • creating, editing, updating in real-time R-shiny apps associated with lab exercises • running statistical analyses of lab
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receive interviews will also be asked for a data analysis code sample (in R, Stata, SPSS, Python, or similar) and 2 references (with ideally at least one of these being an academic/research reference
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cover letter will not be considered. Applicants who receive interviews will also be asked for a data analysis code sample (in R, Stata, SPSS, Python, or similar) and 2 references (with ideally at least
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packages, including STATA, SAS, and/or R • Knowledge of standard internet tools and HTML • Familiarity with standard political science, economics and/or sociology data sources The successful candidate must
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field with core training in foundational & applied aspects of AI/ML. Minimum 5 years of professional experience in an academic, scientific, or R&D environment. A proven track record of publishing original