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data using python. Report results using a variety of scientific, word processing, and presentation platforms. Maintenance and cleaning of additional laboratory equipment and glassware. May instruct other
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working with large-scale behavioral or digital trace data. Strong proficiency in Python (required) and experience with statistical modeling in R or similar environments. Experience designing data pipelines
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coding abilities, including skills in statistical analysis (e.g., R), computational methods (e.g., NLP methods), programming (e.g., Python), online research tools (e.g., Qualtrics) Strong interpersonal
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Server and Active Directory Virtualization (e.g., VMWare) Linux shell scripting Experience with statistical software (e.g., SAS, R, Python) on a research computing cluster is a plus Experience with Ansible
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with computational environments for ’omics data manipulation (command line, Python, R, etc.) * Deep knowledge in at least one relevant subdiscipline, i.e. bioinformatics, microbiology, microbial ecology
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for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R, or Python); Creating and managing very large datasets; Managing and mentoring
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. Basic Qualifications An ideal candidate will have a PhD in computational biology/bioinformatics/statistics/CS or another quantitative field, as well as superb programming (Python, shell scripting) and
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and execute plans for complex and sometimes non-linear work Analytical interest and competence, including experience with quantitative statistical packages in STATA, R and Python. Experience and
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describing: a. Your interest in the position b. The start and end dates for which you would be able to fill this position c. Your familiarity with programing languages (e.g., Stata, SAS, R, Matlab, Python) d
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, representation learning) Spatiotemporal modeling or geospatial/temporal data analysis Medium-to-Large-scale foundation models pretraining/fine-tuning paradigms Strong programming skills in Python and experience