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circumstances while maintaining professional demeanor. (Required) Demonstrated ability to design, and construct Microsoft Access databases, and interact with them using SQL, and R. (Preferred) Demonstrated
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safely. (Required) Availability on Saturdays from 12-9 PM. (Required) Ability to code in R or other statistical programming language. (Preferred) Effectively operate the following equipment:1.Microscope2
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visualization in R and/or Python. Ability to work closely with experimentalists to ensure analyses complement experimental goals and enhance data interpretation. Advanced Computational Skills: Proficiency in
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analysis and handling omics' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance
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' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance computing environments Excellent
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for analyzing questionnaire responses. (Required) Demonstrated proficiency with data analysis software (e.g., SPSS, R, etc.), Microsoft Excel, data management practices, and data visualization tools (e.g
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and procedures for analyzing questionnaire responses. (Required) Demonstrated proficiency with data analysis software (e.g., SPSS, R, etc.), Microsoft Excel, data management practices, and data
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scanners. (Required) Statistical background, basic competence in statistical programming (R, SPSS), and programming skills in R, Python, Psychopy, linux/unix, or shell scripting. (Required) Demonstrated
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next-generation sequencing library preparation and multi-omics analysis is required. Proficiency in shell scripting, Python, and R is expected. A successful candidate(s) will have the following
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statistical programming (SAS, SUDAAN, Stata, SPSS, R), data management and other document processing programs. (Required) Demonstrated ability to work as a team member and to take initiative. (Required