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knowledge of basic statistical principles relevant in medical research. Strong knowledge of clinical trials study design. Evidence of an ability to conduct statistical methods research or investigate
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field One (1) to four (4) years of experience analyzing data using high-performance or cloud-based computing. Knowledge, Skills, and Abilities: Advanced knowledge of basic statistical principles relevant
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quantitative characterization of complex biological samples (cell cultures and tissues). Applying and developing bioinformatics and statistical methods for proteomics data. Instrumentation quality control
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proficient understanding of new areas of research. Good understanding of statistical analyses Ability to work both independently and collaboratively. Self-motivated, detail-oriented, fast learner, highly
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alongside the principal investigator and several team members in several states in the analytic aspects of the research including data management, advanced statistical analyses, and simulation modeling. Key
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Administration), quantitative (e.g., Statistics, Mathematics), or scientific (e.g., Engineering, Psychology) field. Experience may be substituted for the bachelor’s degree requirement on a year-for-year basis
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sciences, data science, machine learning, statistics, mathematics, computer science, or related fields. Preferred Qualifications: Experience in at least one programming language such as Python or R
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laboratory techniques with an emphasis on liquid chromatography and mass spectrometry. Perform experiments and tabulate and analyze data. Prepare reports of quantitative findings including statistical analysis
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candidate will have a passion for collaborative research and will contribute in the areas of study design, data management, a broad range of statistical analysis, and scientific writing (manuscript and grant
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an experimental or wet lab (>6mo full-time). Prior experience with sterile technique. Prior experience with statistical analyses software platforms, bioinformatics platforms, and/or coding in R or Python. Prior