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ecosystem. Identify market gaps across the AI innovation lifecycle, from R&D to commercialization, scale, and adoption, to inform programming and partnership development. Strengthen connections between
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(i.e. machine learning, neural nets, LLMs). Prepare results and design figures for reports and presentations. Manage and manipulate data using requested languages, including Python, R, MATLAB, and STATA
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. Manage and manipulate data using requested languages, including Python, R, MATLAB, and STATA. Collaborate successfully with faculty, students, and other RAs at Princeton as well as external co-authors
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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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Required Knowledge, Skills, Competencies, and Abilities Fluency with statistics, econometrics, and probability theory Good programming skills in python and R -- experience participating in open source
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with significant coursework in economics, mathematics, statistics and/or programming) Experience with statistical programming in STATA and/or R Demonstrated interest in empirical social science Excellent
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. <2 years’ experience in the mechanical design. Experience in a scientific or R&D environment is desirable. Knowledge, Skills and Abilities: Familiarity with simple mechanical design and analysis
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theory Good programming skills in python and R -- experience participating in open source projects a big plus, especially experience with test-driven development BA/BS in Economics, Mathematics
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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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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