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but not limited to Stata and R. Produce summary statistics and conduct basic statistical analyses Writing scripts in python to automate processes and for webscraping Assist with data analysis and
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well as pediatric malignancy. The successful candidate will have experience analyzing data, and proficiency in standard statistical software, including SPSS as well as R. Knowledge of python is a plus. If the
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applied statistics, data science, machine learning, text analysis, and familiarity with coding in R and/or Python. All applications must be submitted through Columbia University?s Academic Search and
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reviews to guide experiment design and identifying emerging methodologies. Processing and analyzing large experimental datasets using scientific computing tools (Python/Matlab). Maintaining laboratory
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detailed documentation. • Develop models and implement program code (STATA, Python, SQL, R, SAS, Matlab, etc.). • Perform statistical analysis, including regression analysis and machine learning techniques
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knowledge of programming, including Linux, Python, and R. Candidates having background knowledge in neuroimaging, machine learning, and/or genomics/genetics are encouraged. Excellent communication and writing
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health, or related field, plus at least two years directly related experience required. Advanced knowledge and proficiency in statistical programming (e.g., R, SAS, Python, Stata) preferred; prior
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in Economics Knowledge of public and environmental economics, as well as causal inference. The ability to code in R and Python. Report writing and presentation. Cleansing and scrubbing large datasets
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science, computer science, biomedical informatics, biostatistics, or related field ? Strong programming skills in Python and/or R ? Experience with machine learning libraries (scikit-learn, TensorFlow
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math, biomedical engineering, physics, or related discipline. Proficiency in programming and data science tools (Python, R, C++, or equivalent). Strong statistical and machine learning background, with