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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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applicants will have:*Expertise conducting spatial and statistical analyses*Experience with scientific computer programming in R and Python*Formal training or experience applying quantitative and spatial
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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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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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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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, processing, and storage, and data analysis. Strong data analysis/visualization skills in R are essential. Required skills / qualifications: Bachelor’s Degree in Psychology, Business, or similar quantitative
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and programming experience (e.g., R or other languages) This one-year appointment is expected to be renewed for a second year based on satisfactory performance and continued funding. Research staff
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English